# Live Broadcasting of High Definition Audiovisual Content Using HDTV over Broadband IP Networks

Authors: C. E. Vegiris; K. A. Avdelidis; C. A. Dimoulas; G. V. Papanikolaou
Journal: International Journal of Digital Multimedia Broadcasting
 (2008)

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## Abstract

The current paper focuses on validating an implementation of a
state-of-the art audiovisual (AV) technologies setup for live broadcasting of cultural shows, via broadband Internet. The main objective of the work was to study, configure, and setup dedicated audio-video equipment for the processes of capturing, processing, and transmission of
extended resolution and high fidelity AV content in order to increase realism and achieve maximum audience sensation. Internet2 and GEANT broadband telecommunication networks were selected as the
most applicable technology to deliver such traffic workloads. Validation procedures were conducted in
combination with metric-based quality of service (QoS) and quality of experience (QoE) evaluation
experiments for the quantification and the perceptual interpretation of the quality achieved during
content reproduction. The implemented system was successfully applied in real-world applications,
such as the transmission of cultural events from Thessaloniki Concert Hall throughout
Greece as well as the reproduction of Philadelphia
Orchestra performances (USA) via Internet2 and GEANT backbones.


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## Body

## 1. Introduction

It is
unquestionable that the rapid evolution  of next generation networks and
broadband access emerging  nowadays has an increased impact on traditional information
and communication  technologies (ICT) services and applications. Among others,
digital multimedia production  and broadcasting is mostly influenced by these
changes, allowing taking full advantage of the contemporary technological
advances. Novel, user-oriented, and on-demand services are currently deployed for
browsing, searching, and retrieval of AV content, including news, multimedia e-learning,
AV streams of cultural events, entertaining shows, and other applications. Web-based
video on demand (VoD) services, digital/interactive TV (DTV/ITV), IP-based TV (IPTV)
programs over Internet and mobile systems are typical examples where AV content
is usually delivered via IP-based topologies [1–7]. This also
complies with the persistent demand for continuous extension of the available
AV content resolution and fidelity, in an effort to achieve better experience,
creating a sense of realism or telepresence [8–19]. High definition
(HD) AV technologies [5–7, 9, 10], Ultra High
Definition Video (UHDV or Super Hi-Vision) [17–19], and digital
cinema (D-cinema) [20] projects are currently focusing on these
objectives, increasing the capacity of the related video streams and raising a
compulsory demand for even higher data transfer rates. Besides the utilities that
have been recently launched in next generation networks architectures [1–3], the combination
of broadband services and high definition multimedia broadcasting is a very
challenging technological/research field that the current paper aims to discuss
in depth.The widespread of
the World Wide Web and the know-how obtained through the successful implementation
of the Internet have
lead to the global adoption of the IP technology and the IP-based communications
over a broad area of contemporary ICT services. There is a worldwide effort to
construct broadband network backbones, like the Internet2 [21] and the Geant [22] initiatives that have been implemented during
the last decade in USA and Europe, respectively. It is obvious that digital
multimedia broadcasting inherently belongs to demanding broadband services such
as the above as well as similar state-of-the art technological approaches [8–10, 21, 22]. The purpose of
the current paper is to analyze, implement, and evaluate the use of state-of-the
art digital multimedia broadcasting technologies in combination with broadband
services for the transmission of demanding AV streams, captured by means of
live performance HDTV shots. The proposed AV configuration setup has been
successfully deployed in real-world applications, such as the transmission of cultural events from
Thessaloniki Concert Hall throughout Greece [23] as well as the reproduction of Philadelphia
Orchestra performances (USA) [24] via Internet2 and GEANT backbone. However, the
presented methodology can be further utilized as guidance in related IPTV applications,
especially those dealing with HD video/multimedia streaming.The paper is
organized as follows. The problem definition is described in Section2, where state
of research and related works are also discussed. Section 3 presents the
proposed system configuration, providing detailed information about the
development steps of the work, all the physical and the technical aspects faced
during the implementation phases, while metrics’ statistics/relation and their utilization
are also considered. Experimental results are analyzed in Section 4, where
evaluation of the adopted system configuration is carried out in combination
with conclusion and future work remarks.


## 2. Problem Definition and Background Work

The increased popularity of networked multimedia applications has
created new demands for reliable and secure video transmission, so that AV
content is expected to account for a large portion of the traffic in the future
Internet and in next-generation wireless systems [8, 25, 26]. This creates
further necessities for broadband networks due to the fact that digital audio
and video hold a large amount of information, especially in critical/demanding
cases, whereas high resolution is required, while quality compromises are not acceptable.
To meet such demands, advanced compression techniques are continuously evolving
in combination with novel routing architectures and algorithms, in an effort to
guarantee the required QoS via the currently available Internet data transfer
rates [8–10, 25, 27, 28]. Classical
examples of this category are the IPTV and VoD projects that have been lanced
during the last years [1–7]. As a
consequence, various studies have been appeared focusing on the evaluation of
the network and the compression parameters, in combination with various content
types, using quantitative metrics (often perceptually adapted) as well as
subjects that incorporate functional, perceptual, and aesthetical mean opinion
scores (MOSs) [8, 27–35]. Recently, research
effort has began focusing on HDTV-related approaches [5–7, 9, 10, 33, 34], including
D-cinema [20] and UHDV [16–19, 36], aiming at evaluating the
advantages, as well as the technical difficulties of these technologies, toward
the implementation of future, AV broadcasting services.The scope of the
current paper is twofold: first, to present a solid system layout for HD video content production and transmission; second, to evaluate various parameters of the system configuration
setup for their effect to the achieved quality. It is important to mention that
the current paper deals with technical issues both at the production (physical
theatre) and reproduction (remote amphitheatre) stages as well as all the
intermediary phases related with content
packaging and streaming (AV formats, compression algorithms, routing
architectures, etc.) Hence, unlike the previously mentioned research works, it
aims at providing
end-to-end solutions and their evaluation for successful broadcasting of live
shows in auditoriums. In addition, audio and surround sound techniques are
essential toward the successful accomplishment of the “high fidelity” target.
Thus, audio-related issues are equally important with video and deserve,
respectively, careful treatment at all the recording, mixing, multiplexing,
coding, and reproduction procedures. Specifically, the problem under study is
best described with commonly raised questions that should be answered.How many cameras and what formats should be
employed? How many microphones, what types, and where should be placed? Which
AV compression, multiplexing, and coding algorithms should be selected? Which
are the most applicable AV content packaging/streaming techniques that should
be implemented in combination with the available network topologies and the
corresponding routing architectures? Is there dedicated AV equipment to fulfill
the reproduction demands, and how should be used? How the above parameters
influence the achieved quality and the perception of the transmitted shows? The outermost target of the current work is
to provide guidance for live AV capturing/IP-broadcasting/reproduction as well
as an integrated methodology for the prediction/estimation of the achieved,
end-to-end QoE (QoEe-e), using QoS metrics (i.e., PSNR) related to both
application-demands (QoSA) and at broadcasting-network level (QoSB).The majority of
the corresponding research works are mainly focused on the video-related issues, which are the
most technically demanding, since they are related to the larger portion of the AV data
stream. For example, CCD-camera noise and lighting-related degradation may
appear in cases where capturing conditions cannot be adjusted based on the
broadcasting demands [8, 37], as the
performed show is mainly designated for the audience at the physical auditorium.
In general, video signals can be corrupted by noise during acquisition,
recording, digitization, processing, and transmission [37]. On the other hand, audio information requires
careful treatment in order to be able to create high fidelity sound-field
reproduction conditions. The importance of this task has been exhaustively
analyzed in D-cinema and UHDV initiatives [13–16, 36], while various
stereo sound recording techniques have been proposed in combination with the
corresponding surround sound systems for its effective implementation [13–16, 36, 38–43]. From a
practical point of view, 5.1 and 7.1 surround systems have prevailed in real-world
application, such as movie theatres and cinema industry. In addition, subjective tests have been applied to provide best
format selection guidance, in combination with the corresponding content type
and the available reproduction HDTV sets [33, 34], while future
trends of HDTV and the third generation of HDTV formats, like the 1080p, have
been studied [9, 10, 34]. However, in the
case of HDTV, little attention was given to the accompanied surround sound in
combination with the viewing distance conditions [9, 11].Considering that
the video compression-related degradation has been studied during the development of the
corresponding algorithms, many researchers are exclusively focused on the
evaluation of the video broadcasting procedures, studying the generated traffic
demands in relation to the characteristics of the involved network technologies [8, 25, 26]. In general,
there are three major research approaches in evaluating broadcasting networks
video-wise: (a) actual video bitrate-based
techniques, (b) video traces-based approaches, and (c) model-based techniques [26, 29–35]. Actual video
streams exhibit originality and provide accurate results during their transmission
evaluation over lossy networks, but raise difficulties connected with their
availability and copyright permissions. In order to overcome such issues, video
traces use only the video content number of bits and the related timing information
instead the video content itself [26, 29, 30]. These
techniques are focusing on the study of the transmission characteristics but
fail to estimate their effect on the decoding process being unable to predict how
the occurred errors reflect on the perception of the received image sequences [26, 29, 30]. An evolution of
the above methods include the design of advanced video traces that incorporate
various video-related features [30], enabling the study
of lost packets influence in compressed sequences [28, 29]. Finally, model-based
video traffic techniques use mathematical models to describe the video
streaming propagation over the network, depending strongly on the validity of
the selected model in a real-world application [26, 29, 30]. These methods
represent the simplest evaluation approaches that provide lost-data statistics
at the level of pixel, frame, and groups of pictures (GOPs), over various
network bandwidths and topologies, different routing architectures, and in general, variable QoS settings [8, 25, 26].As already stated,
packet-loss information is inadequate to estimate the actual video degradation,
related to the received and perceived image quality. In most cases, reference
content is available (full reference (FR) methods [26, 29, 30]), therefore
comparisons between the broadcasted (reference) and the received AV streams are
employed to form the corresponding metrics. Peak signal-to-noise ratio (PSNR)
and mean square error (MSE) are the most common arithmetic metrics that are
usually employed for objective evaluation of “processed” images and videos
(i.e., processes of compression, enhancement/denoising, transmission, etc.) [8, 25–32, 37],
(1)mse(n)=1NH⋅NV∑i,j[x(i,j,n)−y(i,j,n)]2,PSNR(n)=10⋅log10(max(x)2mse(n))=20⋅log10(2nB−1mse(n)),
where x(i,j,n) and y(i,j,n) are the reference and the impaired video frames for the
corresponding video components (i.e., luminance component Y, color
components CR=Y−R, CB=Y−B,R,G,B, etc.),
with i,j the Cartesian image-coordinates, n the frame number, max(x)≡max(y) is the maximum value of the
2D signals that is related to the number of quantization bits nB (equal to 255 for an 8-bit
image signal), NH and NV the horizontal and
vertical image resolution, respectively [8, 32, 37].Although PSNR
metric is quite acceptable for evaluation of integrity of final signal, it is
not capable of evaluating video degradations caused by structural
dissimilarities. A quite simple and “computationally affordable” metric that applies
and is widely used for this task is the perceptually-adapted structural similarity
(SSIM) metric [31] which is extracted based on the general
principle that human vision system (HVS) is highly sensitive to the structural
information of the received optical stimulus. Thus, considering again the
reference and the impaired signals (video-frames) x(i,j,n) and y(i,j,n) a
simplified form to estimate SSIM is given as follows [31]:
(2)SSIM(x,y,n)=(2⋅μx⋅μy)⋅(2+C1)⋅(2σxy+C2)(μx2+μy2+C1)⋅(σx2+σy2+C2),μx=μx(n)=1NH⋅NV∑i,jx(i,j,n),σx=σx(n)=1NH⋅NV∑i,j[x(i,j,n)−μx(n)]2,σxy=σxy(n)=1NH⋅NV∑i,j[x(i,j,n)−μx(n)]⋅[y(i,j,n)−μy(n)]
where μx,σx,σxy are known statistics (mean, standard
deviation, cross-variance), and C1,C2 are small positive constants
that are introduced to prevent computational overflow and instability when
values are very close to zero.Besides FR methods
and their corresponding metrics (PSNR, MSE, SSIM), reduced-reference (RR) and no reference (NR) methods are
employed, when source (reference) content is partially available or unavailable
during the evaluation process [29–31]. These two
approaches are commonly used in combination with subjective tests which are
relying on MOS statistics in order to fully incorporate perceptual attributes
of the HVS during evaluation. In addition, subjective tests are very useful in
cases that the influence of various parameters is not predetermined, or depends
on the characteristics of the AV content itself (i.e., degradations at the
acquisition/digitization phases, impact of packet losses at the decompression
phase, appearance of errors and concealed errors with respect to image position
and motion activity of the content, impact of the selected resolution—scanning to the perceived quality with regard
to content type, etc.) [25–31].To the best of our
knowledge, there are not sufficient guidance and related information on real-world,
end-to-end implementations using state-of-the art audiovisual HD equipment with
the above characteristics, besides the research efforts and demos discussed in
the previous paragraphs that are partially focusing on some of the discussed
objectives. In the current paper scope, statistical analysis was performed using both FR and NR methods, using
standard quality metrics and testing hybrid evaluation functions on real-world
broadcasting and simulated transmission on HD streams.


## 3. The Proposed System Configuration

HD video and
surround sound were the least viable choices to meet the minimum configuration
requirements of the application in question. Additionally, for the specific demands of the current work in
order to be employed in real-world demanding applications, various practical
issues should be considered.


### 3.1. Physical and Technical Issues: Application Demands and Technology Requirements

In order to address the above case, there is a necessity of the
replication of the conditions present in the actual event venue to a potential
virtual event venue. Considering the proportions, a suitably configured
projection hall in a remote site could act as a virtual auditorium following
certain specifications. Fortunately, the high-speed Internet and digital
technology growth during the last years present us with a unique opportunity to combine
all of the above in a digital form following suitable standards and transmit
the content in real time to even the remotest of audiences, satisfying the
uniqueness and motivation needs of an actual cultural event. In the above
frame, our research was targeted to the investigation of the conditions of the
actual venue, the transmission infrastructure, and the virtual venue in terms
of various factors such as actual spectator perception, capturing, transport,
reproduction, and so on. An overview of the architecture used is shown in Figure1(a), while AV capturing/reproduction setups are presented in Figures 1(b) and
1(c), respectively (detailed information about the selected architecture setups
are provided in the following paragraphs).Figure 1
Configuration system setup: (a) architecture overview, (b)
actual venue capture setup (transmission site), (c) indicative virtual hall
configuration (reproduction site).


#### 3.1.1. Capture of The Performances at The Physical Theater: The Transmission Site

The first question that emerges in the design of such a system is the
study of perception, thus the experience of a spectator in a performance hall (auditorium,
concert, opera, etc.). Given the fact that the actual performance is being held
in an organized hall, we take for granted its acoustical and visual integrity.
As a result, audience “sweet spots” exist and are known in each different case.
Thus, if one was to decide a spectator position which would be the experience reference,
a suitable selection would be the choice of one of these spots in terms of both
audio and video stimuli [23, 42, 43]. Our effort was
targeted to the transfer of a selected actual spectator position experience to all
the members of the remote audience [23].In this point, it is useful to discriminate the audio and video
capturing properties. As far as audio is concerned, the perceived result in an
actual hall is produced from the combination of the following factors: (a) the direct
acoustic field, (b) the reverberant acoustic field (hall acoustics), and (c)
the field created by the PA system, if any installed [42, 43]. The
reproduction system in the remote hall was specified to be a standard 5.1
surround system which, nowadays, is the typical sound system installed in the
majority of public projection halls (i.e., cinemas). In order to be able to
reproduce effectively the original audio conditions, it is crucial to acquire
the above fields as isolated as possible so that the final 5.1 mix corresponds to the
experience reference position. For that reason two kinds of microphone setups
were used concurrently: (a) a gun microphone array pointing the stage for the
direct field and (b) a soundfield microphone in the reference position that
holds spatial sound information by means of the four X,Y,Z and W audio
components [40–43] and is used to extract the actual spectator
surround perception (Figure 1(b)).Since the direct field arrives to the spectator with a delay
proportional to the distance from the stage, the above setup is able to provide
the direct field and the reverberant/PA field in the position in question [42, 43]. According to [42, 43], such a hybrid
system is capable of providing soundfield localization, virtual source
positioning-panning and signal enhancement, by means of amplitude weighting and
time delay compensation, especially for the cases of small-sized sources (point
source model) or even still sources. Although these conditions were valid for
most cultural performances dealt in the current project (i.e., jazz, theatrical
acts, recitals, etc.), we decided not to involve sound-source localization for
practical reasons as well as in order to propose a universal recording layout
that could be applied in every cultural show. However, we adopted the amplitude—delay weighting approach, aiming at capturing and reproducing
the audience experience related with the hall acoustic properties of the
physical theatre. Based on the above remarks, the gun microphone array signals
and the corresponding soundfield components were mixed to a 5.1 setup based on
sound propagation criteria (amplitude-phase weighting) according to their
positioning and the coordinates of the capturing (camera) spot [44].As far as the  encoding of the six audio channels that had to be
transmitted is concerned, an AC3 encoder which created a stream of 320 kbits/s,
achieving an easily decodable, high-quality audio form for the consumer side [23]. This is the
encoding that DVB format uses and so it was not further examined because of the
proven quality that provides [45].The case of video is more straightforward as the view of a spectator in
such an environment is limited by the visible field viewing angle and the
boundaries of the stage from the selected position. The most critical point in
this case is that a spectator is able to focus his/her attention to any point
on the stage at any time of the performance. In order to achieve that feeling
in the remote hall, it was necessary to provide the virtual spectators with
full stage view, in adequate quality and at least near-to-real dimensions. The chosen
video capture device (HD-camera) was covering the stage area in a steady
position in order to transfer an unbiased stage aspect (without the
intervention of a director) on the virtual audience [23]. The setup used
in the actual venue is depicted in Figure 1(b).The exact capturing position, meaning the distance from stage and the
height of camera, had to be decided. Specifically, the determination of the
acquisition point strongly depends on the stage’s physical dimensions (width
and height). In addition, special care had to be taken for technical issues,
such as camera lens’s focus length and zoom in order to avoid deformities due
to zoom lenses. In any case, the former set of parameters should be configured
according to the restrictions and limitations of the theater stage and seats’
layout and so it is quite different in each different physical theater.An alternative strategy, regarding live-transmission of audiovisual
(cultural) shows, is to employ a multicamera director-based setup for video and
a 5.1 audio mix independent of the hall acoustic properties, which is being
currently held by the Philadelphia Orchestra with the Global Concert Series [24]. Both strategies
can share identical configuration setups regarding AV broadcasting, however
there are major differences related to the capturing or even the reproduction
layout, issues that have an impact on the achieved QoE, as it will be further commented
in Section 4.The decision of the audiovisual framework was in fact the most crucial
part of the design. The video format finally used was 1080i; however, the 720p
format was also tested. The main reasons for this choice involved the cost and
the consumer side projection capability. The native protocol in the production
side used was the HD-SDI standard in order to eliminate the quality loss before
the transmission [23]. The visual
content was MPEG-2 compressed based on the fact that it is easily decoded,
providing sufficient video quality in the scenario under question. At the time
of investigation, there was a variety of MPEG-2 enabled devices (encoders,
decoders) on the market for a significant amount of time which ensured the
reliability of the method. Moreover, the relatively low bandwidth demands for
this kind of task were able to ensure reliable transmission (given the Internet
framework discussed below). The bitrate chosen was based on subjective,
objective, and empirical criteria and was closely related to the nature of the
transmitted material (a more thorough analysis is presented in Section 3.1.2) [5, 7, 9, 10].Other implementation choices included decisions related to the forward
error correction (ProMPEG FEC), variable/constant bitrate, encoding profile,
and GOP structure. Most of these parameters are under examination by the ITU [46] in relation to the processed content of past
research works [33, 34], taking also
into account the limitations of the transmitting networks. Based on the
low-motion nature of the transmitted content, the final decisions included the
use of Main Profile at High Level (MP@HL) [23] format
of MPEG-2 encoding, CBR mode, and lack of error correction as the less costly
and most easily implemented.


#### 3.1.2. Reproduction at The Remote Auditorium: The Reception Site

According to the audio-recording layout already discussed, it is easy to
describe the corresponding necessities at the remote auditorium. In fact, a
standard 5.1 surround system setup is only required (Figure1(c)), while slight
variation should be occurred related to the dimensions of the remote auditorium
and the adequate number of loudspeakers. In any case, neutral acoustical hall
behavior (low reverberation) is preferred, allowing transfer of the physical
theatre acoustical experience with more fidelity. The sweet spot, in this kind
of environment, is also defined mostly based on the audio quality superimposed
to the conditions of each projection hall.For the video part, the constraint posed is relative to the projection
size. For the biggest degree of realism to be succeeded, the projection of the
event should display the projected objects by their physical dimensions.
Ideally, the size of the projection screen should match the dimensions of physical
theatre stage, but this is not probable to be the case for the remote
auditoriums. Thus, the screen size should be as close as possible to the physical
stage, and of course should not
exceed these physical dimensions. The screen size and the projection resolution
affect the desirable viewing angle to convey the full
sensation of presence which for a wide-field video system is 80–100 arcdeg [11, 12, 17]. In
order to achieve best audience viewing experience, the viewing distance should
be bigger than the shortest distance at which a person with normal vision of
1.0 is unable to recognize the pixel structure on a screen [12]. However, the
sensation of telepresence is decreased as distance increase. A compromise
between the two above conflicting criteria, giving priority to the first, was adopted and recommended for best viewing experience [44].In the remote side the standards used for projection varied according to
the projection equipment among HD-SDI, DVI, XGA, and HDMI due to the
versatility provided by MPEG-2 decoding devices. Although there have been
studies focusing on the subjective evaluation of the HD
format, in combination with the size
of the projection screen in flat TV-sets [33, 34], there are no available published works
focusing on large-auditorium projection. A thorough technology-market research
pointed out as most applicable the use of DLP technology projector, in combination
with over five meter wide, electronic projection screens. As a result, three
alternative projection formats were examined: 720p50, 1080i25, and 1080i29.94,
with the last one applied during reproduction of Philadelphia  Orchestra transmissions [23, 24].


### 3.2. Transport of Av Data and Network Conformation Demands

Most of the attributes describing the transport framework can be derived
from the audiovisual framework specifications. The finally selected choices
included MPEG TS encapsulation using the RTP protocol at the rate of 30 Mbps
combined stream bitrate. This choice was based on the fact that the MPEG TS is
capable of encapsulating
simultaneous audio stream in AC3 format, eliminating the synchronization
problems appeared in past efforts, and allowing the delivery of multichannel
surround sound. Finally, incorporation of RTP introduced an amount of jitter
immunity to the consumers who could take advantage of this capability. Also,
the usage of ProMPEG FEC was tested [23].As previously mentioned, the present Internet attributes motivated the
implementation of the effort in discussion. Following a close collaboration
with GRNET, the concluding
setup was capable of offering
our service reliably to a considerable number of Greek provincial and urban
universities, thus covering a potentially large number of spectators. In order
to service as much interested consumers as possible, the transmissions were
decided to be multicasted through a single group [23]. The connection
provided on the transmission site was established through an M-BGP enabled
switch with an end-to-end optical Gigabit Ethernet uplink to the GRNET backbone
switch and copper wire Gigabit Ethernet downlinks for the internal connections.
The reception side setup inside the university campuses relied on the already
established network infrastructure consisting of copper wire Fast Ethernet wall
sockets of certified functionality and efficiency. The links were tested for
transmission/reception errors and were required to appear high quality link
state which was a relatively easy task since we were addressing to locally
well-organized networks (universities) and not the open public (i.e., home
users). For the transmission case, a stand-alone IGMP enabled MPEG-2
encoder/streamer was used while the reception case required a respective
receiver/decoder which could be consisted of a stand-alone or a pc-based setup.
The multicast traffic was in both cases handled by the Multicast Backbone
(MBONE) infrastructure of the providers involved (GRNET and University NOCs). A
session announcement through SAP was also statically available during the
transmission period in order to encourage participation to our tests. The above
setup ensured the minimization of the physical layer related corruptions.


### 3.3. Qos and Qoe Issues

Quality of service is a term that has been mostly used in network
applications to describe data integrity during transmission, including timely
arrival demands. As already mentioned, in video streaming/broadcasting
application we may distinguish two sequential stages, affecting the overall QoS:
the application QoS (QoSA) and the broadcasting-network QoS (QoSB) [47–49]. This 2-stage model
has been broadly applied in related application [47–49], and it was also
adopted during the experimental phase of the current work for the broadcasting simulation
setups and their statistical analysis (refer to Figure 2). Specifically, in the
application level we may consider the influence of the bitrate [Mbps], input
format [1080i/720p], encoding type [CBR/VBR], content motion activity [motionActivity],
deinterlacing, and error concealment strategy for QoSA. As far as
the network broadcasting level is concerned, the QoSB is influenced
by the network direct packet losses, the jitter, which produces
indirect/secondary packet losses according to the
routing/streaming/buffering/strategy (buffer size, UDP/RTP). In general, QoS
metrics (Qsm) may be configured using the already presented FR metrics PSNR/MSE (use of a single
FR-metric or a combination of them) to evaluate the video quality at each stage.
Hence, given the preceded analysis we may form simple expressions to model Qsm
as function of the application/broadcasting characteristics:
(3)Qsme-e=avrn[Qsme-e(n)]=avrn[f(QsmA,QsmB)],QsmA=fA(encoding,format,content,decoding)=fA(bit-rate,720p/1080i,CBR/VBR,GoP-length,motionActivity,de-interlacing,error  concealement),QsmB=fB(packet  losses,jitter,routing/streaming/buffering/error  correction),
where Qsme-e,
QsmA, and QsmB are the involved end-to-end, application,
and broadcasting QoS metrics, respectively, n is the number of video sequence broadcasted
frames, and f,fA,fB are, in general, complicated
functions aiming to relate the input independent variables (QmA-vars,
QmB-vars) with the QoS estimates.Figure 2
System simulation setup for
performance evaluation by means of QoS and QoE metrics.As already stated,
video stream, packet losses, and PSNR do not reflect linearly on the “video
quality” during reproduction/projection
of the AV broadcasted content, since lost pixels might or
not be visible, and in general have different impact on the perceived QoE [29, 32, 35, 50]. In order to be
able to account for the gained experience and model the QoE, perceptual
criteria related to the HVS should be considered. In the above context, the
simplest rule to express QoE metrics (Qem) as function of the input parameters (QmA-vars, QmB-vars) is to pass all the Qsme-e,
QsmA, QsmB metrics through a filter that emulates the HVS
behavior to obtain the desired Qeme-e, QemA, and QemB.
A different approach would be to deploy perceptually adapted metrics, such as
the SSIM, or even subjective MOS results. Thus, we may replace Qsm and Qem with
the generic expression Qm to parameterize QoS/QoE as function of the corresponding
application and network-oriented QoS/QoE estimates
(4a)Qme-e=f(QmA,QmB)=f[fA(QmA-vars),fB(QmB-vars)],(4b)Qeme-e=f(QemA,QemB)=g(QsmA,QsmB),
where f,fA,fB,g are again nontrivial parametric functions controlled
by the QmA-vars/QmB-vars independent variables (inputs)
previously discussed. According to (4b), the wanted in the current approach is to model the QoE outcomes
as a function of both (QoSA, QoSB) and (QoEA,
QoEB) pairs, expressed by means of PSNR and SSIM, respectively.Let us take a closer inspection to (3), (4a), and (4b), trying to
predict the Qm changes with respect to single-input variations. We will assume
that QoS and QoE are correlated with increasing monotony, so that a Qsm raise (improved
QoS) would reflect to a relative Qem increase (improved QoE), and vice versa.
Hence, we may form simple rules to describe the influence of bitrate, format
(720p/1080i), and content motion activity to the QoSA/QoEA,
and the influence of jitter to the QoSB/QoEB. It is
obvious that as the bitrate increases, QmA get also higher due to
the fact that better image quality is obtained with fewer compression
artifacts. Another issue connected with the bitrate is the content itself. For
instance, the AV streams feature high video motion activity, this makes the
encoding process more demanding and complicated, so that video degradation
worsens in order to be able to attain the desired bandwidth. On the other hand,
increasing the bitrate may cause QmB metrics to decrease, since the
effect of packet losses and jitter to the increasing network-traffic demands is rising. Finally, it is
clear that as the jitter increases the QmB metrics go worse, since
the indirect packet loss rates get higher. The affection of the remaining
parameter is not considered here as less important for the specific demands of the
current application. For instance, CBR/VBR variations were not tested, on the
basis that CBR is more robust and reliable to be deployed in broadband
networks, while deinterlacing and error concealment options were excluded from
the current study for the
sake of simplicity (to avoid confusion by using too many parameters).
Similarly, since direct packet losses are not quite common in broadband
networks, we considered only the influence of jitter. As far as routing
strategies are concerned, it is obvious that the use of RTP is superior over
UDP (related experiments validated this statement), so that the use of RTP was decided
as fixed option. The above remarks could be formalized and expressed by the
following equations:
(5)∂(QmA)∂(bit-rate)>0,∂(QmA)∂(motionActivity)<0,∂(QmB)∂(bit-rate)<0,∂(QmB)∂(jitter)<0,
where the partial derivative ∂(⋅) expresses the influence of each
independent variable, considering that all the other input variables (QmA-vars, QmB-vars) remain unchanged. We may observe that some of
the above changes have complete different impact to the partial system
responses (QmA,QmB), so that none could easily say which
of the above parameters will prevail to the determination of the end-to-end
metrics Qme-e in a nontrivial/realistic broadcasting-configuration
scenario, like the one dealt with
in the current work.Related to the motion activity characteristics is also the use of
interlaced (1080i) or progressive (720p) scanning. For instance, it would be
preferable for a high motion video sequence to be encoded to progressive format
(i.e., 720p) in order to avoid filtering out motion details due to interlaced
scanning (in case of 1080i). Although these motion artifacts are quite annoying and they are
easily perceived by the subjects/spectators, both the FR-metrics PSNR and SSIM
are unable to measure this limitation  due to the fact that it also inherently exists
in the original, source material which is used as reference. Hence, once again
the influence of a single parameter (interlaced/progressive) provides
controversial effects to the overall system behavior. It is important to
mention that the use of 720p and 1080i was not intended for direct comparisons
between the two formats, using the previously mentioned FR-metrics, but they
were proposed as alternative source-content choices to confirm that they both
follow certain rules and pose similar Qm dependencies from the remaining
independent variables (QmA-vars, QmB-vars).Based on the above analysis, evaluation procedures were contacted using
both simulation setups and real video-transmission according to the layout
drawn in Figure2.


## 3.1. Physical and Technical Issues: Application Demands and Technology Requirements

In order to address the above case, there is a necessity of the
replication of the conditions present in the actual event venue to a potential
virtual event venue. Considering the proportions, a suitably configured
projection hall in a remote site could act as a virtual auditorium following
certain specifications. Fortunately, the high-speed Internet and digital
technology growth during the last years present us with a unique opportunity to combine
all of the above in a digital form following suitable standards and transmit
the content in real time to even the remotest of audiences, satisfying the
uniqueness and motivation needs of an actual cultural event. In the above
frame, our research was targeted to the investigation of the conditions of the
actual venue, the transmission infrastructure, and the virtual venue in terms
of various factors such as actual spectator perception, capturing, transport,
reproduction, and so on. An overview of the architecture used is shown in Figure1(a), while AV capturing/reproduction setups are presented in Figures 1(b) and
1(c), respectively (detailed information about the selected architecture setups
are provided in the following paragraphs).Figure 1
Configuration system setup: (a) architecture overview, (b)
actual venue capture setup (transmission site), (c) indicative virtual hall
configuration (reproduction site).


### 3.1.1. Capture of The Performances at The Physical Theater: The Transmission Site

The first question that emerges in the design of such a system is the
study of perception, thus the experience of a spectator in a performance hall (auditorium,
concert, opera, etc.). Given the fact that the actual performance is being held
in an organized hall, we take for granted its acoustical and visual integrity.
As a result, audience “sweet spots” exist and are known in each different case.
Thus, if one was to decide a spectator position which would be the experience reference,
a suitable selection would be the choice of one of these spots in terms of both
audio and video stimuli [23, 42, 43]. Our effort was
targeted to the transfer of a selected actual spectator position experience to all
the members of the remote audience [23].In this point, it is useful to discriminate the audio and video
capturing properties. As far as audio is concerned, the perceived result in an
actual hall is produced from the combination of the following factors: (a) the direct
acoustic field, (b) the reverberant acoustic field (hall acoustics), and (c)
the field created by the PA system, if any installed [42, 43]. The
reproduction system in the remote hall was specified to be a standard 5.1
surround system which, nowadays, is the typical sound system installed in the
majority of public projection halls (i.e., cinemas). In order to be able to
reproduce effectively the original audio conditions, it is crucial to acquire
the above fields as isolated as possible so that the final 5.1 mix corresponds to the
experience reference position. For that reason two kinds of microphone setups
were used concurrently: (a) a gun microphone array pointing the stage for the
direct field and (b) a soundfield microphone in the reference position that
holds spatial sound information by means of the four X,Y,Z and W audio
components [40–43] and is used to extract the actual spectator
surround perception (Figure 1(b)).Since the direct field arrives to the spectator with a delay
proportional to the distance from the stage, the above setup is able to provide
the direct field and the reverberant/PA field in the position in question [42, 43]. According to [42, 43], such a hybrid
system is capable of providing soundfield localization, virtual source
positioning-panning and signal enhancement, by means of amplitude weighting and
time delay compensation, especially for the cases of small-sized sources (point
source model) or even still sources. Although these conditions were valid for
most cultural performances dealt in the current project (i.e., jazz, theatrical
acts, recitals, etc.), we decided not to involve sound-source localization for
practical reasons as well as in order to propose a universal recording layout
that could be applied in every cultural show. However, we adopted the amplitude—delay weighting approach, aiming at capturing and reproducing
the audience experience related with the hall acoustic properties of the
physical theatre. Based on the above remarks, the gun microphone array signals
and the corresponding soundfield components were mixed to a 5.1 setup based on
sound propagation criteria (amplitude-phase weighting) according to their
positioning and the coordinates of the capturing (camera) spot [44].As far as the  encoding of the six audio channels that had to be
transmitted is concerned, an AC3 encoder which created a stream of 320 kbits/s,
achieving an easily decodable, high-quality audio form for the consumer side [23]. This is the
encoding that DVB format uses and so it was not further examined because of the
proven quality that provides [45].The case of video is more straightforward as the view of a spectator in
such an environment is limited by the visible field viewing angle and the
boundaries of the stage from the selected position. The most critical point in
this case is that a spectator is able to focus his/her attention to any point
on the stage at any time of the performance. In order to achieve that feeling
in the remote hall, it was necessary to provide the virtual spectators with
full stage view, in adequate quality and at least near-to-real dimensions. The chosen
video capture device (HD-camera) was covering the stage area in a steady
position in order to transfer an unbiased stage aspect (without the
intervention of a director) on the virtual audience [23]. The setup used
in the actual venue is depicted in Figure 1(b).The exact capturing position, meaning the distance from stage and the
height of camera, had to be decided. Specifically, the determination of the
acquisition point strongly depends on the stage’s physical dimensions (width
and height). In addition, special care had to be taken for technical issues,
such as camera lens’s focus length and zoom in order to avoid deformities due
to zoom lenses. In any case, the former set of parameters should be configured
according to the restrictions and limitations of the theater stage and seats’
layout and so it is quite different in each different physical theater.An alternative strategy, regarding live-transmission of audiovisual
(cultural) shows, is to employ a multicamera director-based setup for video and
a 5.1 audio mix independent of the hall acoustic properties, which is being
currently held by the Philadelphia Orchestra with the Global Concert Series [24]. Both strategies
can share identical configuration setups regarding AV broadcasting, however
there are major differences related to the capturing or even the reproduction
layout, issues that have an impact on the achieved QoE, as it will be further commented
in Section 4.The decision of the audiovisual framework was in fact the most crucial
part of the design. The video format finally used was 1080i; however, the 720p
format was also tested. The main reasons for this choice involved the cost and
the consumer side projection capability. The native protocol in the production
side used was the HD-SDI standard in order to eliminate the quality loss before
the transmission [23]. The visual
content was MPEG-2 compressed based on the fact that it is easily decoded,
providing sufficient video quality in the scenario under question. At the time
of investigation, there was a variety of MPEG-2 enabled devices (encoders,
decoders) on the market for a significant amount of time which ensured the
reliability of the method. Moreover, the relatively low bandwidth demands for
this kind of task were able to ensure reliable transmission (given the Internet
framework discussed below). The bitrate chosen was based on subjective,
objective, and empirical criteria and was closely related to the nature of the
transmitted material (a more thorough analysis is presented in Section 3.1.2) [5, 7, 9, 10].Other implementation choices included decisions related to the forward
error correction (ProMPEG FEC), variable/constant bitrate, encoding profile,
and GOP structure. Most of these parameters are under examination by the ITU [46] in relation to the processed content of past
research works [33, 34], taking also
into account the limitations of the transmitting networks. Based on the
low-motion nature of the transmitted content, the final decisions included the
use of Main Profile at High Level (MP@HL) [23] format
of MPEG-2 encoding, CBR mode, and lack of error correction as the less costly
and most easily implemented.


### 3.1.2. Reproduction at The Remote Auditorium: The Reception Site

According to the audio-recording layout already discussed, it is easy to
describe the corresponding necessities at the remote auditorium. In fact, a
standard 5.1 surround system setup is only required (Figure1(c)), while slight
variation should be occurred related to the dimensions of the remote auditorium
and the adequate number of loudspeakers. In any case, neutral acoustical hall
behavior (low reverberation) is preferred, allowing transfer of the physical
theatre acoustical experience with more fidelity. The sweet spot, in this kind
of environment, is also defined mostly based on the audio quality superimposed
to the conditions of each projection hall.For the video part, the constraint posed is relative to the projection
size. For the biggest degree of realism to be succeeded, the projection of the
event should display the projected objects by their physical dimensions.
Ideally, the size of the projection screen should match the dimensions of physical
theatre stage, but this is not probable to be the case for the remote
auditoriums. Thus, the screen size should be as close as possible to the physical
stage, and of course should not
exceed these physical dimensions. The screen size and the projection resolution
affect the desirable viewing angle to convey the full
sensation of presence which for a wide-field video system is 80–100 arcdeg [11, 12, 17]. In
order to achieve best audience viewing experience, the viewing distance should
be bigger than the shortest distance at which a person with normal vision of
1.0 is unable to recognize the pixel structure on a screen [12]. However, the
sensation of telepresence is decreased as distance increase. A compromise
between the two above conflicting criteria, giving priority to the first, was adopted and recommended for best viewing experience [44].In the remote side the standards used for projection varied according to
the projection equipment among HD-SDI, DVI, XGA, and HDMI due to the
versatility provided by MPEG-2 decoding devices. Although there have been
studies focusing on the subjective evaluation of the HD
format, in combination with the size
of the projection screen in flat TV-sets [33, 34], there are no available published works
focusing on large-auditorium projection. A thorough technology-market research
pointed out as most applicable the use of DLP technology projector, in combination
with over five meter wide, electronic projection screens. As a result, three
alternative projection formats were examined: 720p50, 1080i25, and 1080i29.94,
with the last one applied during reproduction of Philadelphia  Orchestra transmissions [23, 24].


## 3.1.1. Capture of The Performances at The Physical Theater: The Transmission Site

The first question that emerges in the design of such a system is the
study of perception, thus the experience of a spectator in a performance hall (auditorium,
concert, opera, etc.). Given the fact that the actual performance is being held
in an organized hall, we take for granted its acoustical and visual integrity.
As a result, audience “sweet spots” exist and are known in each different case.
Thus, if one was to decide a spectator position which would be the experience reference,
a suitable selection would be the choice of one of these spots in terms of both
audio and video stimuli [23, 42, 43]. Our effort was
targeted to the transfer of a selected actual spectator position experience to all
the members of the remote audience [23].In this point, it is useful to discriminate the audio and video
capturing properties. As far as audio is concerned, the perceived result in an
actual hall is produced from the combination of the following factors: (a) the direct
acoustic field, (b) the reverberant acoustic field (hall acoustics), and (c)
the field created by the PA system, if any installed [42, 43]. The
reproduction system in the remote hall was specified to be a standard 5.1
surround system which, nowadays, is the typical sound system installed in the
majority of public projection halls (i.e., cinemas). In order to be able to
reproduce effectively the original audio conditions, it is crucial to acquire
the above fields as isolated as possible so that the final 5.1 mix corresponds to the
experience reference position. For that reason two kinds of microphone setups
were used concurrently: (a) a gun microphone array pointing the stage for the
direct field and (b) a soundfield microphone in the reference position that
holds spatial sound information by means of the four X,Y,Z and W audio
components [40–43] and is used to extract the actual spectator
surround perception (Figure 1(b)).Since the direct field arrives to the spectator with a delay
proportional to the distance from the stage, the above setup is able to provide
the direct field and the reverberant/PA field in the position in question [42, 43]. According to [42, 43], such a hybrid
system is capable of providing soundfield localization, virtual source
positioning-panning and signal enhancement, by means of amplitude weighting and
time delay compensation, especially for the cases of small-sized sources (point
source model) or even still sources. Although these conditions were valid for
most cultural performances dealt in the current project (i.e., jazz, theatrical
acts, recitals, etc.), we decided not to involve sound-source localization for
practical reasons as well as in order to propose a universal recording layout
that could be applied in every cultural show. However, we adopted the amplitude—delay weighting approach, aiming at capturing and reproducing
the audience experience related with the hall acoustic properties of the
physical theatre. Based on the above remarks, the gun microphone array signals
and the corresponding soundfield components were mixed to a 5.1 setup based on
sound propagation criteria (amplitude-phase weighting) according to their
positioning and the coordinates of the capturing (camera) spot [44].As far as the  encoding of the six audio channels that had to be
transmitted is concerned, an AC3 encoder which created a stream of 320 kbits/s,
achieving an easily decodable, high-quality audio form for the consumer side [23]. This is the
encoding that DVB format uses and so it was not further examined because of the
proven quality that provides [45].The case of video is more straightforward as the view of a spectator in
such an environment is limited by the visible field viewing angle and the
boundaries of the stage from the selected position. The most critical point in
this case is that a spectator is able to focus his/her attention to any point
on the stage at any time of the performance. In order to achieve that feeling
in the remote hall, it was necessary to provide the virtual spectators with
full stage view, in adequate quality and at least near-to-real dimensions. The chosen
video capture device (HD-camera) was covering the stage area in a steady
position in order to transfer an unbiased stage aspect (without the
intervention of a director) on the virtual audience [23]. The setup used
in the actual venue is depicted in Figure 1(b).The exact capturing position, meaning the distance from stage and the
height of camera, had to be decided. Specifically, the determination of the
acquisition point strongly depends on the stage’s physical dimensions (width
and height). In addition, special care had to be taken for technical issues,
such as camera lens’s focus length and zoom in order to avoid deformities due
to zoom lenses. In any case, the former set of parameters should be configured
according to the restrictions and limitations of the theater stage and seats’
layout and so it is quite different in each different physical theater.An alternative strategy, regarding live-transmission of audiovisual
(cultural) shows, is to employ a multicamera director-based setup for video and
a 5.1 audio mix independent of the hall acoustic properties, which is being
currently held by the Philadelphia Orchestra with the Global Concert Series [24]. Both strategies
can share identical configuration setups regarding AV broadcasting, however
there are major differences related to the capturing or even the reproduction
layout, issues that have an impact on the achieved QoE, as it will be further commented
in Section 4.The decision of the audiovisual framework was in fact the most crucial
part of the design. The video format finally used was 1080i; however, the 720p
format was also tested. The main reasons for this choice involved the cost and
the consumer side projection capability. The native protocol in the production
side used was the HD-SDI standard in order to eliminate the quality loss before
the transmission [23]. The visual
content was MPEG-2 compressed based on the fact that it is easily decoded,
providing sufficient video quality in the scenario under question. At the time
of investigation, there was a variety of MPEG-2 enabled devices (encoders,
decoders) on the market for a significant amount of time which ensured the
reliability of the method. Moreover, the relatively low bandwidth demands for
this kind of task were able to ensure reliable transmission (given the Internet
framework discussed below). The bitrate chosen was based on subjective,
objective, and empirical criteria and was closely related to the nature of the
transmitted material (a more thorough analysis is presented in Section 3.1.2) [5, 7, 9, 10].Other implementation choices included decisions related to the forward
error correction (ProMPEG FEC), variable/constant bitrate, encoding profile,
and GOP structure. Most of these parameters are under examination by the ITU [46] in relation to the processed content of past
research works [33, 34], taking also
into account the limitations of the transmitting networks. Based on the
low-motion nature of the transmitted content, the final decisions included the
use of Main Profile at High Level (MP@HL) [23] format
of MPEG-2 encoding, CBR mode, and lack of error correction as the less costly
and most easily implemented.


## 3.1.2. Reproduction at The Remote Auditorium: The Reception Site

According to the audio-recording layout already discussed, it is easy to
describe the corresponding necessities at the remote auditorium. In fact, a
standard 5.1 surround system setup is only required (Figure1(c)), while slight
variation should be occurred related to the dimensions of the remote auditorium
and the adequate number of loudspeakers. In any case, neutral acoustical hall
behavior (low reverberation) is preferred, allowing transfer of the physical
theatre acoustical experience with more fidelity. The sweet spot, in this kind
of environment, is also defined mostly based on the audio quality superimposed
to the conditions of each projection hall.For the video part, the constraint posed is relative to the projection
size. For the biggest degree of realism to be succeeded, the projection of the
event should display the projected objects by their physical dimensions.
Ideally, the size of the projection screen should match the dimensions of physical
theatre stage, but this is not probable to be the case for the remote
auditoriums. Thus, the screen size should be as close as possible to the physical
stage, and of course should not
exceed these physical dimensions. The screen size and the projection resolution
affect the desirable viewing angle to convey the full
sensation of presence which for a wide-field video system is 80–100 arcdeg [11, 12, 17]. In
order to achieve best audience viewing experience, the viewing distance should
be bigger than the shortest distance at which a person with normal vision of
1.0 is unable to recognize the pixel structure on a screen [12]. However, the
sensation of telepresence is decreased as distance increase. A compromise
between the two above conflicting criteria, giving priority to the first, was adopted and recommended for best viewing experience [44].In the remote side the standards used for projection varied according to
the projection equipment among HD-SDI, DVI, XGA, and HDMI due to the
versatility provided by MPEG-2 decoding devices. Although there have been
studies focusing on the subjective evaluation of the HD
format, in combination with the size
of the projection screen in flat TV-sets [33, 34], there are no available published works
focusing on large-auditorium projection. A thorough technology-market research
pointed out as most applicable the use of DLP technology projector, in combination
with over five meter wide, electronic projection screens. As a result, three
alternative projection formats were examined: 720p50, 1080i25, and 1080i29.94,
with the last one applied during reproduction of Philadelphia  Orchestra transmissions [23, 24].


## 3.2. Transport of Av Data and Network Conformation Demands

Most of the attributes describing the transport framework can be derived
from the audiovisual framework specifications. The finally selected choices
included MPEG TS encapsulation using the RTP protocol at the rate of 30 Mbps
combined stream bitrate. This choice was based on the fact that the MPEG TS is
capable of encapsulating
simultaneous audio stream in AC3 format, eliminating the synchronization
problems appeared in past efforts, and allowing the delivery of multichannel
surround sound. Finally, incorporation of RTP introduced an amount of jitter
immunity to the consumers who could take advantage of this capability. Also,
the usage of ProMPEG FEC was tested [23].As previously mentioned, the present Internet attributes motivated the
implementation of the effort in discussion. Following a close collaboration
with GRNET, the concluding
setup was capable of offering
our service reliably to a considerable number of Greek provincial and urban
universities, thus covering a potentially large number of spectators. In order
to service as much interested consumers as possible, the transmissions were
decided to be multicasted through a single group [23]. The connection
provided on the transmission site was established through an M-BGP enabled
switch with an end-to-end optical Gigabit Ethernet uplink to the GRNET backbone
switch and copper wire Gigabit Ethernet downlinks for the internal connections.
The reception side setup inside the university campuses relied on the already
established network infrastructure consisting of copper wire Fast Ethernet wall
sockets of certified functionality and efficiency. The links were tested for
transmission/reception errors and were required to appear high quality link
state which was a relatively easy task since we were addressing to locally
well-organized networks (universities) and not the open public (i.e., home
users). For the transmission case, a stand-alone IGMP enabled MPEG-2
encoder/streamer was used while the reception case required a respective
receiver/decoder which could be consisted of a stand-alone or a pc-based setup.
The multicast traffic was in both cases handled by the Multicast Backbone
(MBONE) infrastructure of the providers involved (GRNET and University NOCs). A
session announcement through SAP was also statically available during the
transmission period in order to encourage participation to our tests. The above
setup ensured the minimization of the physical layer related corruptions.


## 3.3. Qos and Qoe Issues

Quality of service is a term that has been mostly used in network
applications to describe data integrity during transmission, including timely
arrival demands. As already mentioned, in video streaming/broadcasting
application we may distinguish two sequential stages, affecting the overall QoS:
the application QoS (QoSA) and the broadcasting-network QoS (QoSB) [47–49]. This 2-stage model
has been broadly applied in related application [47–49], and it was also
adopted during the experimental phase of the current work for the broadcasting simulation
setups and their statistical analysis (refer to Figure 2). Specifically, in the
application level we may consider the influence of the bitrate [Mbps], input
format [1080i/720p], encoding type [CBR/VBR], content motion activity [motionActivity],
deinterlacing, and error concealment strategy for QoSA. As far as
the network broadcasting level is concerned, the QoSB is influenced
by the network direct packet losses, the jitter, which produces
indirect/secondary packet losses according to the
routing/streaming/buffering/strategy (buffer size, UDP/RTP). In general, QoS
metrics (Qsm) may be configured using the already presented FR metrics PSNR/MSE (use of a single
FR-metric or a combination of them) to evaluate the video quality at each stage.
Hence, given the preceded analysis we may form simple expressions to model Qsm
as function of the application/broadcasting characteristics:
(3)Qsme-e=avrn[Qsme-e(n)]=avrn[f(QsmA,QsmB)],QsmA=fA(encoding,format,content,decoding)=fA(bit-rate,720p/1080i,CBR/VBR,GoP-length,motionActivity,de-interlacing,error  concealement),QsmB=fB(packet  losses,jitter,routing/streaming/buffering/error  correction),
where Qsme-e,
QsmA, and QsmB are the involved end-to-end, application,
and broadcasting QoS metrics, respectively, n is the number of video sequence broadcasted
frames, and f,fA,fB are, in general, complicated
functions aiming to relate the input independent variables (QmA-vars,
QmB-vars) with the QoS estimates.Figure 2
System simulation setup for
performance evaluation by means of QoS and QoE metrics.As already stated,
video stream, packet losses, and PSNR do not reflect linearly on the “video
quality” during reproduction/projection
of the AV broadcasted content, since lost pixels might or
not be visible, and in general have different impact on the perceived QoE [29, 32, 35, 50]. In order to be
able to account for the gained experience and model the QoE, perceptual
criteria related to the HVS should be considered. In the above context, the
simplest rule to express QoE metrics (Qem) as function of the input parameters (QmA-vars, QmB-vars) is to pass all the Qsme-e,
QsmA, QsmB metrics through a filter that emulates the HVS
behavior to obtain the desired Qeme-e, QemA, and QemB.
A different approach would be to deploy perceptually adapted metrics, such as
the SSIM, or even subjective MOS results. Thus, we may replace Qsm and Qem with
the generic expression Qm to parameterize QoS/QoE as function of the corresponding
application and network-oriented QoS/QoE estimates
(4a)Qme-e=f(QmA,QmB)=f[fA(QmA-vars),fB(QmB-vars)],(4b)Qeme-e=f(QemA,QemB)=g(QsmA,QsmB),
where f,fA,fB,g are again nontrivial parametric functions controlled
by the QmA-vars/QmB-vars independent variables (inputs)
previously discussed. According to (4b), the wanted in the current approach is to model the QoE outcomes
as a function of both (QoSA, QoSB) and (QoEA,
QoEB) pairs, expressed by means of PSNR and SSIM, respectively.Let us take a closer inspection to (3), (4a), and (4b), trying to
predict the Qm changes with respect to single-input variations. We will assume
that QoS and QoE are correlated with increasing monotony, so that a Qsm raise (improved
QoS) would reflect to a relative Qem increase (improved QoE), and vice versa.
Hence, we may form simple rules to describe the influence of bitrate, format
(720p/1080i), and content motion activity to the QoSA/QoEA,
and the influence of jitter to the QoSB/QoEB. It is
obvious that as the bitrate increases, QmA get also higher due to
the fact that better image quality is obtained with fewer compression
artifacts. Another issue connected with the bitrate is the content itself. For
instance, the AV streams feature high video motion activity, this makes the
encoding process more demanding and complicated, so that video degradation
worsens in order to be able to attain the desired bandwidth. On the other hand,
increasing the bitrate may cause QmB metrics to decrease, since the
effect of packet losses and jitter to the increasing network-traffic demands is rising. Finally, it is
clear that as the jitter increases the QmB metrics go worse, since
the indirect packet loss rates get higher. The affection of the remaining
parameter is not considered here as less important for the specific demands of the
current application. For instance, CBR/VBR variations were not tested, on the
basis that CBR is more robust and reliable to be deployed in broadband
networks, while deinterlacing and error concealment options were excluded from
the current study for the
sake of simplicity (to avoid confusion by using too many parameters).
Similarly, since direct packet losses are not quite common in broadband
networks, we considered only the influence of jitter. As far as routing
strategies are concerned, it is obvious that the use of RTP is superior over
UDP (related experiments validated this statement), so that the use of RTP was decided
as fixed option. The above remarks could be formalized and expressed by the
following equations:
(5)∂(QmA)∂(bit-rate)>0,∂(QmA)∂(motionActivity)<0,∂(QmB)∂(bit-rate)<0,∂(QmB)∂(jitter)<0,
where the partial derivative ∂(⋅) expresses the influence of each
independent variable, considering that all the other input variables (QmA-vars, QmB-vars) remain unchanged. We may observe that some of
the above changes have complete different impact to the partial system
responses (QmA,QmB), so that none could easily say which
of the above parameters will prevail to the determination of the end-to-end
metrics Qme-e in a nontrivial/realistic broadcasting-configuration
scenario, like the one dealt with
in the current work.Related to the motion activity characteristics is also the use of
interlaced (1080i) or progressive (720p) scanning. For instance, it would be
preferable for a high motion video sequence to be encoded to progressive format
(i.e., 720p) in order to avoid filtering out motion details due to interlaced
scanning (in case of 1080i). Although these motion artifacts are quite annoying and they are
easily perceived by the subjects/spectators, both the FR-metrics PSNR and SSIM
are unable to measure this limitation  due to the fact that it also inherently exists
in the original, source material which is used as reference. Hence, once again
the influence of a single parameter (interlaced/progressive) provides
controversial effects to the overall system behavior. It is important to
mention that the use of 720p and 1080i was not intended for direct comparisons
between the two formats, using the previously mentioned FR-metrics, but they
were proposed as alternative source-content choices to confirm that they both
follow certain rules and pose similar Qm dependencies from the remaining
independent variables (QmA-vars, QmB-vars).Based on the above analysis, evaluation procedures were contacted using
both simulation setups and real video-transmission according to the layout
drawn in Figure2.


## 4. Experimental Results and Discussion

Following the design and the implementation of the system as well as the
related methodology, several applications involving the organization of
transmissions and receptions were
conducted. The experimental transmissions among others included four actual
real-time transmissions from the Thessaloniki Concert Hall (three from the
foyer and one from the main hall). Receiving projection venues was set up in four cities
in Greece (Athens, Thessaloniki, Patras, and Heraklion) and one in EU (Dublin,
Ireland) involving a total of seven virtual halls varying from very small to
medium size. The decoding devices we encouraged the organizers to set up and
finally used were PC-based decoders using the VLC Media Player, whereas the
case of hardware decoding was only tested by our team. The acceptance of the
audience was quite encouraging for this kind of activities and was expressed by
the increasing number of spectators and the desire to continue to provide the
service.We also tested the proposed methodology concerning the virtual hall
arrangement via the organization of two public projections of the Global
Concert Series, considering also the organizational aspects of such an event.
Several promotional acts were taken (TV promotional videos, posters,
invitations, etc.) in order to stimulate and measure the public interest on the
subject. After the event, the spectators were asked to fill in a questionnaire
in order to measure certain experience factors. The similar results to the ones
received from our own transmissions are quite promising. A more exhaustive
analysis of the parameter selection and the tests conducted is presented below.


### 4.1. Quantitative Analysis by Means of Metric-Based Evaluation

Before any NR qualitative evaluation, FR methods were also enabled
aiming at evaluating
the video degradation issues by means of metric-extracted objective quantities.
This evaluation procedure was carried out only for the video content due to the
fact that audio coding/multiplexing was based on a well-tested technology
(AC-3) that has been successfully implemented [45] during the last decades. However, the
evaluation of the new recording layout is worthwhile, and this is why
audio-related subjective tests were included in the qualitative evaluation
procedure during content reproduction at the remote site(s) (this issue is
further analyzed in the next paragraph). In addition, more thoroughly
subjective evaluation, in combination with quantitative analysis and the
adoption/definition of appropriate audio-metrics, is currently scheduled.As far as it concerns video evaluation, uncompressed HD video content [33, 34, 51] was selected as reference material in order to
be compared with the received/decompressed video at the simulated remote site. In general, the evaluation procedure had to be carried according to the following
variables: (a) content type, (b) compression parameters, (c) streaming
parameters, and (d) routing/QoS settings. The first category divides content into two major categories
according to the original HDTV format (720p,1080i). Five subcategories are
formed for each format type, based on the involved motion activity of the
content, which implies pace of action [33, 34]. The involved “Sverige Television AB” (SVT) reference video set has been used in the past for similar
evaluation in HDTV-related application [33, 34] and this is an additional reason for its
selection that enriches its suitability for the demands of the current
application. The 10 different content
type reference videos were edited separately for each format and two
different video clips were produced, one 720p sequence and one 1080i sequence.
Each content type was used three times in each sequence and between the
different content types a grey mate of 2 seconds was added. The five different
content types were ranked by the motion activity that they contain by us. They
were graded in a scale from 1 to5, with 1 being the one containing the smallest
motion activity.Besides content type, the compression parameters provide an additional
variable that determines the encoding bitrate. Given the use of MPEG-2
compression, three different bitrates were involved during simulations (high=18.1Mbps, moderate=17Mbps, and low=15Mbps), these values were selected as
recommended and used as reference from IPTV Focus Group of ITU [23, 25–29]. Other
parameters of compression like CBR versus VBR, type, and length of GOP as already stated were not further examined [23]. However, the unavoidable network layer issues
were put under investigation in order to balance the factors of video stream
bitrate/protocol versus quality in jitter conditions. By definition, jitter is
the variation presented in trip time from a transmitter to a receiver leading
to the deterioration of the stream quality especially in the case of
synchronization sensitive services such as the multimedia applications. It is
also highly dependent of the network topology of a packet switching
infrastructure. Since in the Internet framework the network complexity and
therefore the jitter involved is increased as the geographic distances of the
venues grow, it is crucial to investigate this factor in the current context.As for the streaming parameters, the protocol selection (UDP versus RTP)
was the only variable involved given that the MPEG2-TS formation was used. The
superiority of RTP is rather obvious that the use of it is preferable, whenever
this is possible. Nevertheless, the presence of extra buffering memory that RTP
implies is a cost proportional to the transmitted stream bitrate that cannot be
unnoticed. Especially in cases of streams of high bitrates like the ones we
transmit, the extra cost of using RTP is quite significant and so it is
supposed to be the second, more costly choice, after UDP. Since RTP actually
adds a predefined immunity of certain milliseconds of jitter, according to the buffer size
used, the relation of the jitter effects between RTP and UDP can be expressed
by the following equations:(6)QsmB(jitterms)|RTP={QsmB(jitterms−bufferms)|UDP,jitterms>bufferms,max{QsmB},jitterms≤bufferms,bufferms≈8000⋅bufferMBbitrateMBps≈8000⋅bufferMB⋅compression_ratioH⋅V⋅bpp⋅fps,
where H,V are the horizontal
and vertical video resolution, respectively, bpp stands for bits per pixel, fps for frames per second, and compression_ratio is the ratio of the original versus the compressed stream size. Due to the above, the case of UDP,
which may be used for general conclusions, was examined.The network performance was simulated by the NETEM
(NETwork EMulator) module [52] which can be totally parameterized. Network latency
was set at constant typical value of 50 milliseconds as it does not affect the
one way transmission quality except the addition of a constant delay. The value
of jitter (latency variation) was used as a control variable using values of 0,0.05,0.09,0.11, and 0.12 milliseconds. As a result, 30 different simulations
(2 resolution formats × 3 bitrates × 5 jitter) had to be implemented, in
order for all the possible combinations to be recorded. For this purpose, fifteen
different hypothetical reference circuits (HRCs) were used which are presented
in Table 1.Table 1
The HRC profiles
that were tested during quantitative evaluation.
HRCBitrateJitter115 Mbps0217 Mbps0318.1 Mbps0415 Mbps0.05517 Mbps0.05618.1 Mbps0.05715 Mbps0.09817 Mbps0.09918.1 Mbps0.091015 Mbps0.111117 Mbps0.111218.1 Mbps0.111315 Mbps0.121417 Mbps0.121518.1 Mbps0.12One high performance windows-based PC, equipped with an HD-SDI video
card and a high data transfer rate striped disk array was used as player for
playing the reference video clips. A Linux-based PC with NETEM module installed was used as the
network simulator and finally the capturing of projected video was done by
another PC similar to the first. The encoding and decoding were done by the standard
Tandberg encoder-decoder system used in all transmissions. For compatibility
reasons, the set of reference video contents that was used was converted and edited by taking
special care about not having any quality degradations during the whole
pretransmission process. The format that was used was uncompressed YUV 4:2:2
8-bit in AVI file container. The coded and transmitted video signals had to be edited
and converted to the same format in order for the comparisons to be done.
Editing of the captured video was mandatory since both recording softwares that we tried
were unable to synchronize at once with the playback system through network
connection.The comparison and evaluation of transmitted video signals were done with Semaca’s
software VQLab [53] which can extract the PSNR and SSIM metrics of
each video signal compared to a reference video. Both metrics were extracted once
for the video degradation (Qme-e and QmA) caused
by each HRC end-to-end, using as references the original played content videos
and once for video degradation (QmB) caused just by the network using as reference
the video produced right after the codec system. The latter is the video signal
coded and transmitted by an ideal network (jitter and packet loss are zero) and so it
coincides with the video produced from systems HRC 1, 2, and 3 for different
coding bitrates.The modeling ofQme-e as a function of QmA and QmB is our intention as we have already stated in Section 3.3. By the extracted
values of PSNR and SSIM metrics of HRCs 1, 2, and 3 (Jitter=0) QmA can be modeled as a function of
bitrate. In Figure 3 the graphs of experimental data are presented where the logarithmic trend of them can be seen. A
logarithmic function is also used in [49] for standard definition video SSIM modelling and
so it may be assumed that the relation of quality metrics and bitrate can be
described by the following equation in the case of high definition too:
(7)y=a1⋅ln(x)+a2.
By using our experimental data and the Levenberg-Marquardt
algorithm for nonlinear curve fitting in LabVIEW 7.1, we calculated the coefficients of this function
for each different content type and for both metrics. The two equations for
each metric are as follows:
(8)SSIMA=as1⋅ln(bitrate)+as2,PSNRA=ap1⋅ln(bitrate)+ap2.
The model works fine for all content types as it can be seen from the
mean errors and the standard deviations of it, which are presented in Table 2. All the coefficients for each content type can be
viewed in Table 3.Table 2
Mean errors and standard deviations of model forQmA.
720p1080iSSIMPSNRSSIMPSNRMotion activityMean errorError STDMean errorError STDMean errorError STDMean errorError STD14.81265E-90.004135222.18991E-110.2287544.73121E-90.006481275.64537E-90.3264124.47919E-90.01112514.70308E-90.7631414.13375E-90.01354288.15997E-90.96744234.02524E-90.007621551.12177E-110.3781393.49324E-90.01214621.80827E-80.37319643.95311E-90.02807751.19821E-111.070113.34799E-90.03339771.96567E-81.0088853.99949E-90.02147231.22118E-110.9279633.16903E-90.03777951.54833E-81.10852Table 3
Coefficients for the
model ofQmA.
QmA_Model720p1080iSSIMPSNRSSIMPSNRMotion activityαs1αs2αp1αp2αs1αs2αp1αp210.03054310.8295542.1807930.19130.03661210.7991942.4160229.970820.05977330.7208242.0992529.65750.08617790.6247562.5194228.503830.09599240.5930173.2408621.12990.1377780.4408844.1646418.527440.1001190.585823.6897419.8220.1490510.3940543.921418.961550.09559350.5823482.9198520.56020.1640420.3386073.9805817.3714Graphs of the samples and mean curves of experimental
data for the modelQmA.
(a)(b)(c)(d)Following the same strategy,QmB can be modeled from the measured
PSNR and SSIM values of HRCs 6, 9, 12, and 15 as a
function of jitter using as reference the measurements of HRC 3. Based on the observed
logarithmic decay of the readings as can be viewed in Figure 4, the following exponential
equation was initially used:
(9)y=b0+b1⋅eb2⋅x.
By applying our
experimental data to the previously mentioned method, we calculated the
coefficients of this function for each different content type and for both
metrics. The two equations for each metric are presented as follows:
(10)SSIMB1=bs0+bs1⋅ebs2⋅(jitter),PSNRB1=bp0+bp1⋅ebp2⋅(jitter).
The evaluation of
the above model, through the examination of the mean errors and the standard
deviations, showed undesirable behavior for the case of PSNR, which provided
concrete evidence for the model-data incompatibility. However, this model
proved to be acceptable for the case of SSIM for both cases of 720p and 1080i.
These remarks are evident in Table 4. All the
coefficients for each content type can be viewed in Table 5.Table 4
Mean errors and standard deviations of model forQmB1.
720p1080iSSIMSSIMMotion activityMean errorError STDMean errorError STD1−8.48932E-130.0940386−1.06714E-120.1062022−3.39184E-130.128918−2.24342E-110.1402983−5.36862E-130.148489−1.01207E-110.1577174−1.4043E-110.174185−4.34895E-120.1700755−1.26526E-120.157883−2.00221E-110.180327Table 5
Coefficients for the first
model ofQmB.
QmB_Model1
(SSIM)720p1080iMotion activitybs0bs1bs2bs0bs1bs211.04583623.413−0.002894631.05583741.162−0.0033235921.07585985.212−0.003017091.06958799.006−0.0040442131.06874964.321−0.002800151.08267968.93−0.0040320841.07646919.701−0.003214251.09661365.86−0.0032957751.097151303.84−0.002900831.0961076.83−0.00420267Graphs of the samples and
mean curves of experimental data for the modelQmB2.
(a)(b)(c)(d)To overcome the
instability of the above model in the case of PSNR, a linear mixture of
exponential models was tested, which was expressed by the following equation:(11)y=∑k=0Kbk⋅exp(k⋅x),K=3.
Thus, the
resulting equations were formed to the following and the fitting was based on
the least squares algorithm using
the LabVIEW 7.1 environment, for each different content type and for both
metrics:
(12)SSIMB2=∑k=0Kbsk⋅exp(k⋅(jitter)),K=3,PSNRB2=∑k=0Kbpk⋅exp(k⋅(jitter)),K=3.
The above model presented acceptable behavior for the SSIM case as well
as for the PSNR case of 1080i, but failed to adequately model the PSNR case of
720p, the fact that is evident from the mean errors and
the standard deviations of the second QmB model fitting in Table 6. All the coefficients
for each content type can be viewed in Tables 7 and 8.Table 6
Mean errors and standard deviations of model forQmB2.
720p1080iSSIMPSNRSSIMPSNRMotion activityMean errorError STDMean errorError STDMean errorError STDMean errorError STD19.12609E-110.0541336−1.63586E-95.328561.87671E-100.0688297.62564E-92.857621.7857E-110.0724123−3.20952E-93.553761.0412E-100.08629273.33925E-93.0807439.23496E-110.1138491.8E-814.06333.42642E-110.1051273.10354E-93.0068543.83357E-110.117794−1.57997E-99.959726.21223E-110.1283922.04578E-92.799595−2.00853E-110.09634836.46447E-119.184322.01423E-100.1154571.85578E-93.13145Table 7
Coefficients for the second
model ofQmB.
QmB_Model
2-720pSSIMPSNRMotion activitybs0bs1bs2bs3bp0bspbp2bp31−46725.1176095−248735156070736328−2.65946E+63.59846E+6−2.16142E+62−10470.140397.6−58424.9375411.36928E+6−5.02405E+66.90881E+6−4.21977E+63−46514.1175285−247582155348−7.54831E+62.8292E+7−3.97343E+72.47832E+74−120208451941−636803398563−3.19986E+61.19944E+7−1.68435E+71.0503E+758717.2−31553.142673.6−25544.3−2646295574.4−12502670375.6Table 8
Coefficients for the
second model ofQmB.
QmB_Model 2-1080iSSIMPSNRMotion activitybs0bs1bs2bs3bp0bspbp2bp31109072−408678573804−3578015.07703E+6−1.89401E+72.64827E+7−1.64484E+72172349−646148907766−5663985.06641E+6−1.89048E+72.64395E+7−1.64257E+73169289−634746891844−5565204.23374E+6−1.57846E+72.2059E+7−1.36947E+7476416.1−286047401204−2498892.66162E+6−9.88401E+61.37599E+7−8.51072E+65201941−7571691.06384E+6−6638424.28908E+6−1.59895E+72.23434E+7−1.38702E+7Finally, as far as the end-to-end model is
concerned, a function combining the results of subsystems A and B as defined in (4a) and (4b)
is needed. From (2),
it can be proven that the values of SSIM range from (0-1) according to
the similarity of the original and the processed video frame. Moreover, the subsystems
A and B are connected in cascade resulting in additive deterioration of the
image quality related to the behavior of each. Based on the above remarks, the
proposed model of the end-to-end system for the SSIM metric was defined by the
following function:
(13)SSIMe-e=SSIMA⋅SSIMB.
On the other hand, the PSNR metric is a logarithmic measure expressed in dB as
presented in (1). Therefore, the final
result of the end-to-end metric is in fact the superimposition of the partial
subsystems metrics, in which the minimum value is defined from the minimum
partial value. This is similar to the superimposition applied to the
uncorrelated sound sources for the calculation of the equivalent sound pressure
level [54] as follows:
(14)LEQ=10⋅log10∑k=1K10Lk/10.
In our case, the
calculation formula based on (14) is transformed to the
following:
(15)PSNRe-e=−10⋅log10(10−PSNRA/10+10−PSNRB/10).
The functions (13)
and (15)
were applied to the observations of all the HRCs defined in Table 1 for 720p, 1080i and the combination of the two
and the results are summarized in Table 9.Table 9
Mean errors and standard deviations of model forQme-e.
End-to-end quality metricSSIMPSNRTest setError meanError STDError meanError STDALL0.020.030.450.73720p0.020.020.370.621080i0.030.040.590.87


### 4.2. Qualitative Evaluation

After examining
the whole set of possible parameters of the system that can define its
performance and taking into account all the restrictions, a core system
configuration was chosen which was to be under minor changes. This
configuration was based in the conclusions of other relevant research, as well
as in economical and practical reasons. The implementation of technologies that
have already been tested and evaluated separately or respectively to other use
was decisive in proceeding to real-world experiments. So the chance to evaluate
system’s performance by transmitting or receiving real-world events was given.As it has already
been stated, three transmissions and two receptions have taken place by us.
From the first three transmissions, useful conclusions have been conducted,
respectively, to the potentials of the system. Alternative formats, recording
techniques and equipment were tested and the results were promising about the
feasibility of the system and there have been also interest by the potential
audience wherever projection has taken place in big auditorium (University of Patras). The audience accepted the
projections of events with enthusiasm and the feeling of high-definition video
and surround sound was noticeable and positive evaluated by everyone. The use
of just one camera was evaluated positive too and in any case not monotonic, in
spite of the fact that the size of the screen was smaller than the recommended.The reception of
two transmissions from the Global Concerts Series by the Philadelphia Orchestra
gave us the chance to evaluate systems performance one more time and compare a
different approach in a fully controlled projection site and by a survey that
was conducted in a larger group of people. Although the use of just one camera
was not the case in these transmissions, the rest of the transmission system
was almost identical to the one we used so the survey’s results can be useful
for the evaluation.The network over
which the transmission has taken place provided a high bandwidth of 100 Mbps
and a very high QoS. Thus, the encoder’s bitrate was 18 Mbps, the transmitting
format 1080i25 with MP@HL(4:2:0) profile and the packet formation protocol UDP.
The other parameters for reasons that have already been mentioned were constant
bitrate (CBR), IBBP format for GOP, and a relatively low length of 12 frames.
The encoder that was used was Tandberg E5280 with HD expansion module, as
decoder was used mainly Tandberg T1228 decoder and secondary VLC software
installed in PC and a DLP-technology projector was used.With this
configuration in the cases of one transmission and one reception, 56 people
participated in the survey and completed questionnaires. The subjects were not
experts and were randomly selected. They were given the questionnaires before
the projection or in the break and supplement it at the end. The instructions given
were to read it in advance in order to ensure the worst case scenario. This is
because the subjects after reading the questions concentrated and paid
attention even for minor quality degradation. The subjects were asked among
others to characterize the total quality of video and audio separately using a
five-degree quality scale and also to evaluate the quality degradations. The
scale that was used is similar to the one proposed by ITU for single stimulus continuous quality evaluation (SSCQE) [32–34, 55]. Moreover, they were asked about the total experience of watching
an event by this way and had to answer how much realistic they have found the
projection. Another question was, if they would like to watch another event,
what was their motive to watch it and what improvements they would suggest?
From the validation tests, three subjects were rejected for inconsistent
answers or incomplete questions.The results
presented in Figure5 show that in both cases, the transmission from
Thessaloniki and from Philadelphia, the subjects evaluated the quality of video
as “very good” or “excellent,” more than 80% and the quality of sound more than
70%. Most of the subjects, more than 60%, evaluated the degradations and
impairments of the video and audio as “perceptible, but not annoying” or “imperceptible.”
Lastly, the total experience of the event was evaluated as “very realistic” or “interesting”
by more than 70%.Qualitative evaluation results: (a) video quality (b) sound quality (c) perceptibility of errors and impairments (d) total experience.
(a)
Video_quality(b)
Sound_quality(c)
Error_perceptibility(d)
ExperienceIt is obvious that
the results are influenced by the “hollow effect.” This can be explained by the
fact that the audience was for the first time watching a transmission like
this. However, the percentages of positive answers were very high to be caused
just by that effect. Another interesting finding was that comparing the answers
of the subjects answering in the first survey (transmission) the frequency of
answering “Realistic” in the evaluation of the total experience was higher than
the relative one in the second survey (reception). The small size of the
samples in both surveys results in a big confidence interval for the
percentages of answers “realistic” so we can assume that there is a trend by
the audience to evaluate the use of just one camera more realistic. This can be
claimed once all the other parameters were identical in both cases and the
relative percentages have a quite big difference in favor of the first
transmission and consequently of the one camera use. In order to prove the
validity of this statement, a more elaborate survey is necessary.Figure6 represents the spatial distribution of subjects’
answers in the case of the second survey. The respective results of the first
survey cannot be evaluated because of the size of the sample. A1 is located in
front of the left part of the projection screen facing the audience. It may be observed
the distribution of subjects, respectively, and the evaluation of several
parameters. It is obvious from Figure 6(c) that the subjects sited near the minimum viewing
distance evaluated the video quality better than the ones in front or behind of
them. This figure in combination with Figure 6(e) proves that sitting closer than the
minimum viewing distance, the viewing experience decreases and the video errors
and impairments are more perceptible. Figure 6(d) reveals that because of the
poor acoustic performance of the remote auditorium, the listening experience
was better close to the loudspeakers which were besides the screen and at the
back of side walls.Subjective evaluation (5-degree level: from 0—“poor” to 4—“excellent”) of
the result throughout the projection venue (A1 is located in front of the left
part of the projection screen facing the audience): (a) samples distribution, (b)
total experience, (c) video quality, (d) audio quality, and (e) perception of
specific video errors.
(a)(b)(c)(d)(e)


### 4.3. Conclusion and Further Work

The purpose of the
current work was to implement and evaluate HDTV over IP technologies in
real-world multimedia-broadcasting applications, for the live transmission of
cultural events via broadband networks (such as Internet2 and Geant backbones).
Various evaluation procedures were conducted in combination with network simulations
and different configuration setups, before the finally selected architecture
was decided and deployed. The
soundness of the current work stems from the fact that similar experimentation
procedures have not been considered for specific “enhanced reality”
applications, such as e-learning, teleworking, telecollaboration, and others. The
proposed system was enthusiastically accepted by the audience, proving to be
feasible and reliable. The adopted methodology to use a single-still camera in
combination with large projection screen and theater-adapted surround sound seems to provide increased
realism. Given the above scenario combined with the optimization tests that we
conducted, resulted to the specification of minimal requirements (bitrate, jitter)
for such a task. Specifically, CBR encoding of 18 Mbps UDP in jitter conditions
of 0.10 millisecond
substantiated to be a minimal choice for high-quality transmission, although
further experimentation could lead to more optimal utilization of network
resources and increased tolerance to QoS variations. For instance, the use of additional
combinations of VBR, ProMPEG FEC for today’s MPEG-2, different compression
formats (MPEG-4, WMV, etc.), various types and lengths of GOP, and lower/higher
bitrates are under consideration. The potential of full interaction of the
system is another issue.Furthermore, a more elaborate investigation of transmission modeling was
made based on simulations of hypothetical reference circuits (HRCs). The
creation of a conditional model setup showed the feasibility of end-to-end
performance estimation from the distinct properties of two subsystems regarding
the encoding process (logarithmic curve fitting) and the transmission process
(exponential mixture curve fitting), respectively. The model presented
acceptable performance for all the cases except from the case of network
subsystem PSNR modelling
for the case of 720p which calls for further investigation. Also, a qualitative
evaluation of the applied system is presented, proving the assumptions made
during the design process mostly regarding the physical aspects of the project.
Evolutions of the present model could include the incorporation of such subjective tests and perceptually adapted metrics into the performance definition QoS/QoE of a
system, the extension of the properties for the subsystem parameterization as
well as audio performance estimation.In any case, we may conclude that the impact of broadband networks in
digital multimedia broadcasting, like the one described, will bring a new era
to the cultural and educational world prospects.


## 4.1. Quantitative Analysis by Means of Metric-Based Evaluation

Before any NR qualitative evaluation, FR methods were also enabled
aiming at evaluating
the video degradation issues by means of metric-extracted objective quantities.
This evaluation procedure was carried out only for the video content due to the
fact that audio coding/multiplexing was based on a well-tested technology
(AC-3) that has been successfully implemented [45] during the last decades. However, the
evaluation of the new recording layout is worthwhile, and this is why
audio-related subjective tests were included in the qualitative evaluation
procedure during content reproduction at the remote site(s) (this issue is
further analyzed in the next paragraph). In addition, more thoroughly
subjective evaluation, in combination with quantitative analysis and the
adoption/definition of appropriate audio-metrics, is currently scheduled.As far as it concerns video evaluation, uncompressed HD video content [33, 34, 51] was selected as reference material in order to
be compared with the received/decompressed video at the simulated remote site. In general, the evaluation procedure had to be carried according to the following
variables: (a) content type, (b) compression parameters, (c) streaming
parameters, and (d) routing/QoS settings. The first category divides content into two major categories
according to the original HDTV format (720p,1080i). Five subcategories are
formed for each format type, based on the involved motion activity of the
content, which implies pace of action [33, 34]. The involved “Sverige Television AB” (SVT) reference video set has been used in the past for similar
evaluation in HDTV-related application [33, 34] and this is an additional reason for its
selection that enriches its suitability for the demands of the current
application. The 10 different content
type reference videos were edited separately for each format and two
different video clips were produced, one 720p sequence and one 1080i sequence.
Each content type was used three times in each sequence and between the
different content types a grey mate of 2 seconds was added. The five different
content types were ranked by the motion activity that they contain by us. They
were graded in a scale from 1 to5, with 1 being the one containing the smallest
motion activity.Besides content type, the compression parameters provide an additional
variable that determines the encoding bitrate. Given the use of MPEG-2
compression, three different bitrates were involved during simulations (high=18.1Mbps, moderate=17Mbps, and low=15Mbps), these values were selected as
recommended and used as reference from IPTV Focus Group of ITU [23, 25–29]. Other
parameters of compression like CBR versus VBR, type, and length of GOP as already stated were not further examined [23]. However, the unavoidable network layer issues
were put under investigation in order to balance the factors of video stream
bitrate/protocol versus quality in jitter conditions. By definition, jitter is
the variation presented in trip time from a transmitter to a receiver leading
to the deterioration of the stream quality especially in the case of
synchronization sensitive services such as the multimedia applications. It is
also highly dependent of the network topology of a packet switching
infrastructure. Since in the Internet framework the network complexity and
therefore the jitter involved is increased as the geographic distances of the
venues grow, it is crucial to investigate this factor in the current context.As for the streaming parameters, the protocol selection (UDP versus RTP)
was the only variable involved given that the MPEG2-TS formation was used. The
superiority of RTP is rather obvious that the use of it is preferable, whenever
this is possible. Nevertheless, the presence of extra buffering memory that RTP
implies is a cost proportional to the transmitted stream bitrate that cannot be
unnoticed. Especially in cases of streams of high bitrates like the ones we
transmit, the extra cost of using RTP is quite significant and so it is
supposed to be the second, more costly choice, after UDP. Since RTP actually
adds a predefined immunity of certain milliseconds of jitter, according to the buffer size
used, the relation of the jitter effects between RTP and UDP can be expressed
by the following equations:(6)QsmB(jitterms)|RTP={QsmB(jitterms−bufferms)|UDP,jitterms>bufferms,max{QsmB},jitterms≤bufferms,bufferms≈8000⋅bufferMBbitrateMBps≈8000⋅bufferMB⋅compression_ratioH⋅V⋅bpp⋅fps,
where H,V are the horizontal
and vertical video resolution, respectively, bpp stands for bits per pixel, fps for frames per second, and compression_ratio is the ratio of the original versus the compressed stream size. Due to the above, the case of UDP,
which may be used for general conclusions, was examined.The network performance was simulated by the NETEM
(NETwork EMulator) module [52] which can be totally parameterized. Network latency
was set at constant typical value of 50 milliseconds as it does not affect the
one way transmission quality except the addition of a constant delay. The value
of jitter (latency variation) was used as a control variable using values of 0,0.05,0.09,0.11, and 0.12 milliseconds. As a result, 30 different simulations
(2 resolution formats × 3 bitrates × 5 jitter) had to be implemented, in
order for all the possible combinations to be recorded. For this purpose, fifteen
different hypothetical reference circuits (HRCs) were used which are presented
in Table 1.Table 1
The HRC profiles
that were tested during quantitative evaluation.
HRCBitrateJitter115 Mbps0217 Mbps0318.1 Mbps0415 Mbps0.05517 Mbps0.05618.1 Mbps0.05715 Mbps0.09817 Mbps0.09918.1 Mbps0.091015 Mbps0.111117 Mbps0.111218.1 Mbps0.111315 Mbps0.121417 Mbps0.121518.1 Mbps0.12One high performance windows-based PC, equipped with an HD-SDI video
card and a high data transfer rate striped disk array was used as player for
playing the reference video clips. A Linux-based PC with NETEM module installed was used as the
network simulator and finally the capturing of projected video was done by
another PC similar to the first. The encoding and decoding were done by the standard
Tandberg encoder-decoder system used in all transmissions. For compatibility
reasons, the set of reference video contents that was used was converted and edited by taking
special care about not having any quality degradations during the whole
pretransmission process. The format that was used was uncompressed YUV 4:2:2
8-bit in AVI file container. The coded and transmitted video signals had to be edited
and converted to the same format in order for the comparisons to be done.
Editing of the captured video was mandatory since both recording softwares that we tried
were unable to synchronize at once with the playback system through network
connection.The comparison and evaluation of transmitted video signals were done with Semaca’s
software VQLab [53] which can extract the PSNR and SSIM metrics of
each video signal compared to a reference video. Both metrics were extracted once
for the video degradation (Qme-e and QmA) caused
by each HRC end-to-end, using as references the original played content videos
and once for video degradation (QmB) caused just by the network using as reference
the video produced right after the codec system. The latter is the video signal
coded and transmitted by an ideal network (jitter and packet loss are zero) and so it
coincides with the video produced from systems HRC 1, 2, and 3 for different
coding bitrates.The modeling ofQme-e as a function of QmA and QmB is our intention as we have already stated in Section 3.3. By the extracted
values of PSNR and SSIM metrics of HRCs 1, 2, and 3 (Jitter=0) QmA can be modeled as a function of
bitrate. In Figure 3 the graphs of experimental data are presented where the logarithmic trend of them can be seen. A
logarithmic function is also used in [49] for standard definition video SSIM modelling and
so it may be assumed that the relation of quality metrics and bitrate can be
described by the following equation in the case of high definition too:
(7)y=a1⋅ln(x)+a2.
By using our experimental data and the Levenberg-Marquardt
algorithm for nonlinear curve fitting in LabVIEW 7.1, we calculated the coefficients of this function
for each different content type and for both metrics. The two equations for
each metric are as follows:
(8)SSIMA=as1⋅ln(bitrate)+as2,PSNRA=ap1⋅ln(bitrate)+ap2.
The model works fine for all content types as it can be seen from the
mean errors and the standard deviations of it, which are presented in Table 2. All the coefficients for each content type can be
viewed in Table 3.Table 2
Mean errors and standard deviations of model forQmA.
720p1080iSSIMPSNRSSIMPSNRMotion activityMean errorError STDMean errorError STDMean errorError STDMean errorError STD14.81265E-90.004135222.18991E-110.2287544.73121E-90.006481275.64537E-90.3264124.47919E-90.01112514.70308E-90.7631414.13375E-90.01354288.15997E-90.96744234.02524E-90.007621551.12177E-110.3781393.49324E-90.01214621.80827E-80.37319643.95311E-90.02807751.19821E-111.070113.34799E-90.03339771.96567E-81.0088853.99949E-90.02147231.22118E-110.9279633.16903E-90.03777951.54833E-81.10852Table 3
Coefficients for the
model ofQmA.
QmA_Model720p1080iSSIMPSNRSSIMPSNRMotion activityαs1αs2αp1αp2αs1αs2αp1αp210.03054310.8295542.1807930.19130.03661210.7991942.4160229.970820.05977330.7208242.0992529.65750.08617790.6247562.5194228.503830.09599240.5930173.2408621.12990.1377780.4408844.1646418.527440.1001190.585823.6897419.8220.1490510.3940543.921418.961550.09559350.5823482.9198520.56020.1640420.3386073.9805817.3714Graphs of the samples and mean curves of experimental
data for the modelQmA.
(a)(b)(c)(d)Following the same strategy,QmB can be modeled from the measured
PSNR and SSIM values of HRCs 6, 9, 12, and 15 as a
function of jitter using as reference the measurements of HRC 3. Based on the observed
logarithmic decay of the readings as can be viewed in Figure 4, the following exponential
equation was initially used:
(9)y=b0+b1⋅eb2⋅x.
By applying our
experimental data to the previously mentioned method, we calculated the
coefficients of this function for each different content type and for both
metrics. The two equations for each metric are presented as follows:
(10)SSIMB1=bs0+bs1⋅ebs2⋅(jitter),PSNRB1=bp0+bp1⋅ebp2⋅(jitter).
The evaluation of
the above model, through the examination of the mean errors and the standard
deviations, showed undesirable behavior for the case of PSNR, which provided
concrete evidence for the model-data incompatibility. However, this model
proved to be acceptable for the case of SSIM for both cases of 720p and 1080i.
These remarks are evident in Table 4. All the
coefficients for each content type can be viewed in Table 5.Table 4
Mean errors and standard deviations of model forQmB1.
720p1080iSSIMSSIMMotion activityMean errorError STDMean errorError STD1−8.48932E-130.0940386−1.06714E-120.1062022−3.39184E-130.128918−2.24342E-110.1402983−5.36862E-130.148489−1.01207E-110.1577174−1.4043E-110.174185−4.34895E-120.1700755−1.26526E-120.157883−2.00221E-110.180327Table 5
Coefficients for the first
model ofQmB.
QmB_Model1
(SSIM)720p1080iMotion activitybs0bs1bs2bs0bs1bs211.04583623.413−0.002894631.05583741.162−0.0033235921.07585985.212−0.003017091.06958799.006−0.0040442131.06874964.321−0.002800151.08267968.93−0.0040320841.07646919.701−0.003214251.09661365.86−0.0032957751.097151303.84−0.002900831.0961076.83−0.00420267Graphs of the samples and
mean curves of experimental data for the modelQmB2.
(a)(b)(c)(d)To overcome the
instability of the above model in the case of PSNR, a linear mixture of
exponential models was tested, which was expressed by the following equation:(11)y=∑k=0Kbk⋅exp(k⋅x),K=3.
Thus, the
resulting equations were formed to the following and the fitting was based on
the least squares algorithm using
the LabVIEW 7.1 environment, for each different content type and for both
metrics:
(12)SSIMB2=∑k=0Kbsk⋅exp(k⋅(jitter)),K=3,PSNRB2=∑k=0Kbpk⋅exp(k⋅(jitter)),K=3.
The above model presented acceptable behavior for the SSIM case as well
as for the PSNR case of 1080i, but failed to adequately model the PSNR case of
720p, the fact that is evident from the mean errors and
the standard deviations of the second QmB model fitting in Table 6. All the coefficients
for each content type can be viewed in Tables 7 and 8.Table 6
Mean errors and standard deviations of model forQmB2.
720p1080iSSIMPSNRSSIMPSNRMotion activityMean errorError STDMean errorError STDMean errorError STDMean errorError STD19.12609E-110.0541336−1.63586E-95.328561.87671E-100.0688297.62564E-92.857621.7857E-110.0724123−3.20952E-93.553761.0412E-100.08629273.33925E-93.0807439.23496E-110.1138491.8E-814.06333.42642E-110.1051273.10354E-93.0068543.83357E-110.117794−1.57997E-99.959726.21223E-110.1283922.04578E-92.799595−2.00853E-110.09634836.46447E-119.184322.01423E-100.1154571.85578E-93.13145Table 7
Coefficients for the second
model ofQmB.
QmB_Model
2-720pSSIMPSNRMotion activitybs0bs1bs2bs3bp0bspbp2bp31−46725.1176095−248735156070736328−2.65946E+63.59846E+6−2.16142E+62−10470.140397.6−58424.9375411.36928E+6−5.02405E+66.90881E+6−4.21977E+63−46514.1175285−247582155348−7.54831E+62.8292E+7−3.97343E+72.47832E+74−120208451941−636803398563−3.19986E+61.19944E+7−1.68435E+71.0503E+758717.2−31553.142673.6−25544.3−2646295574.4−12502670375.6Table 8
Coefficients for the
second model ofQmB.
QmB_Model 2-1080iSSIMPSNRMotion activitybs0bs1bs2bs3bp0bspbp2bp31109072−408678573804−3578015.07703E+6−1.89401E+72.64827E+7−1.64484E+72172349−646148907766−5663985.06641E+6−1.89048E+72.64395E+7−1.64257E+73169289−634746891844−5565204.23374E+6−1.57846E+72.2059E+7−1.36947E+7476416.1−286047401204−2498892.66162E+6−9.88401E+61.37599E+7−8.51072E+65201941−7571691.06384E+6−6638424.28908E+6−1.59895E+72.23434E+7−1.38702E+7Finally, as far as the end-to-end model is
concerned, a function combining the results of subsystems A and B as defined in (4a) and (4b)
is needed. From (2),
it can be proven that the values of SSIM range from (0-1) according to
the similarity of the original and the processed video frame. Moreover, the subsystems
A and B are connected in cascade resulting in additive deterioration of the
image quality related to the behavior of each. Based on the above remarks, the
proposed model of the end-to-end system for the SSIM metric was defined by the
following function:
(13)SSIMe-e=SSIMA⋅SSIMB.
On the other hand, the PSNR metric is a logarithmic measure expressed in dB as
presented in (1). Therefore, the final
result of the end-to-end metric is in fact the superimposition of the partial
subsystems metrics, in which the minimum value is defined from the minimum
partial value. This is similar to the superimposition applied to the
uncorrelated sound sources for the calculation of the equivalent sound pressure
level [54] as follows:
(14)LEQ=10⋅log10∑k=1K10Lk/10.
In our case, the
calculation formula based on (14) is transformed to the
following:
(15)PSNRe-e=−10⋅log10(10−PSNRA/10+10−PSNRB/10).
The functions (13)
and (15)
were applied to the observations of all the HRCs defined in Table 1 for 720p, 1080i and the combination of the two
and the results are summarized in Table 9.Table 9
Mean errors and standard deviations of model forQme-e.
End-to-end quality metricSSIMPSNRTest setError meanError STDError meanError STDALL0.020.030.450.73720p0.020.020.370.621080i0.030.040.590.87


## 4.2. Qualitative Evaluation

After examining
the whole set of possible parameters of the system that can define its
performance and taking into account all the restrictions, a core system
configuration was chosen which was to be under minor changes. This
configuration was based in the conclusions of other relevant research, as well
as in economical and practical reasons. The implementation of technologies that
have already been tested and evaluated separately or respectively to other use
was decisive in proceeding to real-world experiments. So the chance to evaluate
system’s performance by transmitting or receiving real-world events was given.As it has already
been stated, three transmissions and two receptions have taken place by us.
From the first three transmissions, useful conclusions have been conducted,
respectively, to the potentials of the system. Alternative formats, recording
techniques and equipment were tested and the results were promising about the
feasibility of the system and there have been also interest by the potential
audience wherever projection has taken place in big auditorium (University of Patras). The audience accepted the
projections of events with enthusiasm and the feeling of high-definition video
and surround sound was noticeable and positive evaluated by everyone. The use
of just one camera was evaluated positive too and in any case not monotonic, in
spite of the fact that the size of the screen was smaller than the recommended.The reception of
two transmissions from the Global Concerts Series by the Philadelphia Orchestra
gave us the chance to evaluate systems performance one more time and compare a
different approach in a fully controlled projection site and by a survey that
was conducted in a larger group of people. Although the use of just one camera
was not the case in these transmissions, the rest of the transmission system
was almost identical to the one we used so the survey’s results can be useful
for the evaluation.The network over
which the transmission has taken place provided a high bandwidth of 100 Mbps
and a very high QoS. Thus, the encoder’s bitrate was 18 Mbps, the transmitting
format 1080i25 with MP@HL(4:2:0) profile and the packet formation protocol UDP.
The other parameters for reasons that have already been mentioned were constant
bitrate (CBR), IBBP format for GOP, and a relatively low length of 12 frames.
The encoder that was used was Tandberg E5280 with HD expansion module, as
decoder was used mainly Tandberg T1228 decoder and secondary VLC software
installed in PC and a DLP-technology projector was used.With this
configuration in the cases of one transmission and one reception, 56 people
participated in the survey and completed questionnaires. The subjects were not
experts and were randomly selected. They were given the questionnaires before
the projection or in the break and supplement it at the end. The instructions given
were to read it in advance in order to ensure the worst case scenario. This is
because the subjects after reading the questions concentrated and paid
attention even for minor quality degradation. The subjects were asked among
others to characterize the total quality of video and audio separately using a
five-degree quality scale and also to evaluate the quality degradations. The
scale that was used is similar to the one proposed by ITU for single stimulus continuous quality evaluation (SSCQE) [32–34, 55]. Moreover, they were asked about the total experience of watching
an event by this way and had to answer how much realistic they have found the
projection. Another question was, if they would like to watch another event,
what was their motive to watch it and what improvements they would suggest?
From the validation tests, three subjects were rejected for inconsistent
answers or incomplete questions.The results
presented in Figure5 show that in both cases, the transmission from
Thessaloniki and from Philadelphia, the subjects evaluated the quality of video
as “very good” or “excellent,” more than 80% and the quality of sound more than
70%. Most of the subjects, more than 60%, evaluated the degradations and
impairments of the video and audio as “perceptible, but not annoying” or “imperceptible.”
Lastly, the total experience of the event was evaluated as “very realistic” or “interesting”
by more than 70%.Qualitative evaluation results: (a) video quality (b) sound quality (c) perceptibility of errors and impairments (d) total experience.
(a)
Video_quality(b)
Sound_quality(c)
Error_perceptibility(d)
ExperienceIt is obvious that
the results are influenced by the “hollow effect.” This can be explained by the
fact that the audience was for the first time watching a transmission like
this. However, the percentages of positive answers were very high to be caused
just by that effect. Another interesting finding was that comparing the answers
of the subjects answering in the first survey (transmission) the frequency of
answering “Realistic” in the evaluation of the total experience was higher than
the relative one in the second survey (reception). The small size of the
samples in both surveys results in a big confidence interval for the
percentages of answers “realistic” so we can assume that there is a trend by
the audience to evaluate the use of just one camera more realistic. This can be
claimed once all the other parameters were identical in both cases and the
relative percentages have a quite big difference in favor of the first
transmission and consequently of the one camera use. In order to prove the
validity of this statement, a more elaborate survey is necessary.Figure6 represents the spatial distribution of subjects’
answers in the case of the second survey. The respective results of the first
survey cannot be evaluated because of the size of the sample. A1 is located in
front of the left part of the projection screen facing the audience. It may be observed
the distribution of subjects, respectively, and the evaluation of several
parameters. It is obvious from Figure 6(c) that the subjects sited near the minimum viewing
distance evaluated the video quality better than the ones in front or behind of
them. This figure in combination with Figure 6(e) proves that sitting closer than the
minimum viewing distance, the viewing experience decreases and the video errors
and impairments are more perceptible. Figure 6(d) reveals that because of the
poor acoustic performance of the remote auditorium, the listening experience
was better close to the loudspeakers which were besides the screen and at the
back of side walls.Subjective evaluation (5-degree level: from 0—“poor” to 4—“excellent”) of
the result throughout the projection venue (A1 is located in front of the left
part of the projection screen facing the audience): (a) samples distribution, (b)
total experience, (c) video quality, (d) audio quality, and (e) perception of
specific video errors.
(a)(b)(c)(d)(e)


## 4.3. Conclusion and Further Work

The purpose of the
current work was to implement and evaluate HDTV over IP technologies in
real-world multimedia-broadcasting applications, for the live transmission of
cultural events via broadband networks (such as Internet2 and Geant backbones).
Various evaluation procedures were conducted in combination with network simulations
and different configuration setups, before the finally selected architecture
was decided and deployed. The
soundness of the current work stems from the fact that similar experimentation
procedures have not been considered for specific “enhanced reality”
applications, such as e-learning, teleworking, telecollaboration, and others. The
proposed system was enthusiastically accepted by the audience, proving to be
feasible and reliable. The adopted methodology to use a single-still camera in
combination with large projection screen and theater-adapted surround sound seems to provide increased
realism. Given the above scenario combined with the optimization tests that we
conducted, resulted to the specification of minimal requirements (bitrate, jitter)
for such a task. Specifically, CBR encoding of 18 Mbps UDP in jitter conditions
of 0.10 millisecond
substantiated to be a minimal choice for high-quality transmission, although
further experimentation could lead to more optimal utilization of network
resources and increased tolerance to QoS variations. For instance, the use of additional
combinations of VBR, ProMPEG FEC for today’s MPEG-2, different compression
formats (MPEG-4, WMV, etc.), various types and lengths of GOP, and lower/higher
bitrates are under consideration. The potential of full interaction of the
system is another issue.Furthermore, a more elaborate investigation of transmission modeling was
made based on simulations of hypothetical reference circuits (HRCs). The
creation of a conditional model setup showed the feasibility of end-to-end
performance estimation from the distinct properties of two subsystems regarding
the encoding process (logarithmic curve fitting) and the transmission process
(exponential mixture curve fitting), respectively. The model presented
acceptable performance for all the cases except from the case of network
subsystem PSNR modelling
for the case of 720p which calls for further investigation. Also, a qualitative
evaluation of the applied system is presented, proving the assumptions made
during the design process mostly regarding the physical aspects of the project.
Evolutions of the present model could include the incorporation of such subjective tests and perceptually adapted metrics into the performance definition QoS/QoE of a
system, the extension of the properties for the subsystem parameterization as
well as audio performance estimation.In any case, we may conclude that the impact of broadband networks in
digital multimedia broadcasting, like the one described, will bring a new era
to the cultural and educational world prospects.



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*Source: 250654-2009-02-01.xml*