Globecom 2014 - Communications Software, Services and Multimedia Symposium

Multi-view Video Streaming with Mobile Cameras
Shiho Kodera∗ , Takuya Fujihashi† , Shunsuke Saruwatari∗ , Takashi Watanabe†∗ Faculty of Informatics, Shizuoka University, Japan† Graduate School of Information Science and Technology, Osaka University, Japan

Abstract—Multi-view video system includes three sections:acquisition, transmission, and display. This paper focuses on theacquisition of multi-view video. Existing multi-view video acquisition studies exploit multi-camera arrays mutually connectedby wires. However, this imposes the limitations of places andobjects. To overcome the limitations, we exploit multiple mobile
cameras and wireless networks for multi-view video acquisition.
The acquisition of the multi-view video needs to achieve a
reduction in video traffic while maintaining high video quality
for communication between mobile cameras and an access point.
This paper proposes Multi-view Video Streaming with Mobile
Cameras (MVS/MC) to satisfy these requirements. MVS/MC
has two features: packet overhearing and transmission ordercontrol. First, each mobile camera overhears other cameras’ video
packets, and encodes its own video frames using the overheard
video packets. Second, the access point controls the transmission
order of the mobile cameras, thus realizing bidirectional interview prediction. Bidirectional inter-view prediction exploits theinter-camera domain correlation among the mobile cameras tofurther remove the redundant information. Evaluations using
multi-view video sequences show that, compared with existing
methods, MVS/MC reduces the volume of traffic with only a slightdegradation in video quality. For example, MVS/MC reduces
traffic by 52 % compared to existing methods when PSNR is
36 dB.

I.

I NTRODUCTION

The development of 3D video technology has led toa new scene representation technique known as multi-view
video. Multi-view video provides an immersive perception of
a 3D scene, and has paved the way for many emerging 3D
applications, such as free viewpoint video [1], [2], 3DTV, andimmersive teleconferencing [3].
Figure 1 shows the structure of a multi-view video system. The acquisition section captures a scene using multiple
synchronized cameras located at different spatial locations(viewpoints). The transmission section encodes the resulting
video sequences, and transmits them to the display section,
which displays the 3D scene.

[15] and 3D warping [16], while FTV [2] and integral 3D
television [17] are display-level approaches.
Earlier studies of video acquisition exploit multi-camera
arrays. A multi-camera array consists of multiple cameras thatare mutually connected by wires. This imposes a limitation on
multi-camera arrays, as it makes it inherently difficult to takethe cameras outdoors to capture a scene.
To overcome this limitation, the present paper exploits
wireless networks and mobile cameras for multi-view video
acquisition. Multi-view video acquisition using wireless networks has two requirements: a reduction in network traffic, andhigh video quality. These requirements affect user satisfaction
and application quality.
To this end, we propose Multi-view Video Streaming with
Mobile Cameras (MVS/MC). MVS/MC has two features:
packet overhearing, and transmission order control. First, each
mobile camera overhears other cameras’ communication, andreceives the cameras’ video frames. Each mobile camera
encodes its own video frames with the overheard video frames,
thus reducing the volume of video traffic. Second, an accesspoint controls the order in which the mobile cameras transmit
data. The transmission order enables bidirectional inter-view
prediction among the mobile cameras, and this achieves further
traffic reduction. Evaluations using a JMVC encoder andthe MERL benchmark test sequences reveal that MVS/MC
achieves low traffic volume with only a slight degradation invideo quality.
The remainder of this paper is organized as follows. Section
II presents a summary of current multi-view video acquisition
techniques. We describe the concept of MVS/MC in Section
III. In Section IV, we report the results of evaluations thatreveal the reduction in traffic volume and measure the video
quality of the proposed MVS/MC. Finally, our conclusions are
summarized in Section V.

A number of transmission technologies have been developed. For instance, Multi-view Video Coding (MVC) was
issued as an amendment to H.264/MPEG-4 AVC [4]–[6], andInteractive Multi-view Video Streaming (IMVS) reduces multiview video traffic for stored and playback streaming [7], [8].
User Dependent Multi-view Video Transmission (UDMVT)
reduces multi-view video traffic for live streaming [9]–[11],and User dependent Multi-view video Streaming for Multi-user(UMSM) reduces multi-view video traffic for live streamingwith multiple users [12]–[14].
Previous studies into the display of multi-view video focus
on either the decoder or the display. Typical decoder-levelstudies of image display include depth image-based rendering

978-1-4799-3512-3/14/$31.00 ©2014 IEEE

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Network
Accesspoint

Acquisition
sectionFig. 1.

Multi-view system

Decoder

Encoder

TransmissionsectionViewer

Display
sectionGlobecom 2014 - Communications Software, Services and Multimedia Symposium

II.

M ULTI - VIEW V IDEO ACQUISITION

Multi-view video acquisition over wireless networks enables us to view indoor/outdoor scenes from every angle via
freely switchable viewpoints. Users can create a 3D videousing multi-view video sequences. Figure 2 shows the systemmodel of multi-view video acquisition with wireless networks.
Several mobile cameras are connected to an access point
through these wireless networks, and the access point isconnected to an encoder by a wired network. Each mobile
camera transmits its own video frames to the access point.
Once the access point has received video frames from multiple
mobile cameras, it transmits the received video frames to theencoder.
To play a multi-view video smoothly, the acquisition system should satisfy two requirements. The first is that thevolume of video traffic is sufficiently low to allow effective
transmission over the wireless network. The amount of multiview video traffic is greater than that of single-view video.
In simple terms, the volume of N -view video traffic is N
times greater than that of single-view video. However, wirelessnetworks have a lower data rate than wired networks, becauseof their narrow bandwidth and interference. When mobile
cameras transmit multi-view video over wireless networks, thelow data rate increases the transmission delay between themobile cameras and the access point. Long transmission delays
will frustrate users.
The second requirement is the maintenance of high video
quality. The video quality effectively measures the degree ofvideo degradation that has been decoded from the raw video.
Maintaining high video quality represents a trade-off with theaim of reducing video traffic. If the degradation is small,the acquisition system is applicable to numerous applications.
However, high video quality necessitates a high volume ofvideo traffic.
The simplest method for realizing multi-view video acquisition with wireless networks involves each mobile cameratransmitting its own video to the access point independently.
However, the data rate of wireless networks decreases when
multiple mobile cameras transmit to the access point, as the
bandwidth is shared among the cameras. This induces longtransmission delays, leading to low user satisfaction.
Video traffic can be reduced if each mobile camera degrades the frame rate and the quantization parameter of its
own video. The quantization parameter indirectly represents
the relation between video traffic and quality. When the quantization parameter is high, the original values in each video
frame are more likely to be quantized to zeroes. However, notsurprisingly, this degradation induces low video quality.
One method of reducing video traffic and maintaining
high video quality is Distributed Multi-view Video Coding(DMVC) [18]–[20]. DMVC is an encoding-level approachthat exploits the inter-camera domain correlation for multiview video streaming over wireless networks. DMVC exploits
distributed source coding for encoding, and transmits video
with side information. This side information includes thecamera position and angle. Distributed source coding achieves
the same compression ratio, as each mobile camera encodesits own video using video from other mobile cameras. Typical1413

Accesspoint

Encoder

Mobile cameras

Fig. 2.

Multi-view video acquisition with wireless networks

theories of distributed source coding are Slepian–Wolf theory[21] and Wyner–Ziv theory [22].
III.

M ULTI - VIEW V IDEO S TREAMING WITH M OBILEC AMERAS (MVS/MC)

To satisfy the two requirements discussed in Section II,
we propose MVS/MC. MVS/MC exploits a feature of wirelessnetworks whereby a node can overhear packets transmitted by
its neighbors. Each camera node reduces its own video traffic
by calculating the differences between its own video and theoverheard video. MVS/MC is a transmission-level approach,although it can be combined with an encoding-level approachsuch as DMVC [18]–[20].
A. Overview of MVS/MC
MVS/MC requires initialization, transmission order control, encoding, transmission, and decoding.
1)

2)

3)
4)

5)

When a mobile camera enters the communication
area of an access point, the mobile camera starts theprocess of initialization. The details of initialization
are described in Section III-B.
After each mobile camera has been initialized, theaccess point determines their transmission order. The
transmission order decision is based on positional
information of each mobile camera, which is received
during initialization. The access point then broadcasts
the transmission order to the mobile cameras. The
details of transmission order control are described in
Section III-C.
Each mobile camera encodes its own video using
video overheard from other mobile cameras. The
details of encoding are described in Section III-D.
A mobile camera transmits the encoded video in
one Group of Pictures (GOP) to the access pointaccording to the received transmission order. EachGOP is a video frame set, typically consisting of eightframes. Other mobile cameras overhear the transmitted video. After one GOP has been transmitted byeach mobile camera, the access point determines thetransmission order for the next GOP. The details ofvideo transmission are described in Section III-E.
The video received by the mobile cameras or theaccess point is decoded by a standard H.264/AVC
decoder. The details of decoding are described in
Section III-F.

B. Initialization
Before video transmission, an access point assigns a unique
ID to each mobile camera. The access point periodicallyGlobecom 2014 - Communications Software, Services and Multimedia Symposium

TABLE I.
Parameters, functions
Corder[i]size (C)N OTATION

mobile camera y needs to overhear two video sequences
before its own transmission. The first video sequence is thatfrom mobile camera x. The second is the video from thecamera closest to mobile camera y and does not assign thetransmission order. Following the above conditions, the accesspoint selects mobile camera z, and determines the transmission
order from mobile camera x → mobile camera z → mobile
camera y in order. The transmission order realizes bidirectional
inter-view prediction. After the order has been determined, theaccess point regards mobile camera z as mobile camera x, andrepeats the above process to determine the transmission orderamong the other cameras so as to realize bidirectional interview prediction.

Description
Mobile camera ID set
in the communication area of the access point
Mobile camera ID array
Number of elements in set C

Mobile camera1

Mobile camera2
Mobile camera3

If size (C) is 0, mobile camera y is not able to encode its
own video by bidirectional inter-view prediction. In this case,the access point determines that y is the last camera to transmit
its video. The access point then terminates transmission ordercontrol, and broadcasts the transmission order to all mobile
cameras.

Accesspoint
Fig. 3.

Example showing three mobile cameras

transmits a beacon packet to its own communication area,
informing the mobile cameras they have entered this region.
When a mobile camera receives a beacon packet, it returns
information on its own position and is assigned a unique ID
by the access point. The position information is based on GPS
data.
C. Transmission order control
To reduce the amount of redundant information passed
among the mobile cameras, the access point determines theirtransmission order based on the positional information. The
transmission order is based on bidirectional inter-view prediction in H.264/AVC. Bidirectional inter-view prediction uses theinter-camera domain correlation among the mobile cameras tofurther reduce the redundant information [4]–[6].
We explain the transmission order control procedure for N
mobile cameras within the communication area of an accesspoint. Table I describes the notation used in the Algorithm.
The algorithm consists of two parts: a starting mobile camera
decision and a transmission order decision. For the starting
mobile camera decision, the access point determines which
mobile camera is first to transmit its own video to the accesspoint. The starting mobile camera x is farthest from the accesspoint.
For the transmission order decision, the access point determines the subsequent transmission order for all mobile
cameras. When mobile cameras are positioned so as to usebidirectional prediction, the access point outputs a transmission order that realizes bidirectional inter-view prediction.
To determine the transmission order, the access point first
selects mobile camera y that is closest to the starting mobile
camera x. The access point then calculates size (C) to confirm
that mobile camera y is able to encode its own video withbidirectional inter-view prediction using other mobile cameras’video.
If size (C) is greater than or equal to 1, mobile camera yis able to encode its own video using bidirectional inter-view
prediction. To exploit the bidirectional inter-view prediction,

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We assume that there are three mobile cameras in thecommunication area of an access point. Figure 3 shows the
positional relation of the mobile cameras and the access point.
The set C consists of the IDs of mobile cameras 1, 2, and3. The access point regards mobile camera 1 as the starting
mobile camera, because this is farthest from the access point.
The access point sets the ID of mobile camera 1 to order[1],and removes this ID from C because the starting mobile
camera first transmits its own video to the access point. Next,
the access point selects the ID of mobile camera 2, which is
closest to camera 1, from C. The access point removes mobile
camera 2’s ID from C and calculates size (C). The result ofsize (C) represents the number of mobile cameras that have notbeen assigned a transmission order. Because size (C) is 1, theaccess point selects mobile camera 3 from C. Mobile camera
3 is the closest to mobile camera 2 of the mobile cameras in
C. The access point sets mobile camera 3’s ID to order[2] andmobile camera 2’s ID to order[3] to realize bidirectional interview prediction for mobile camera 2’s encoding. The accesspoint removes mobile camera 3’s ID from C and calculates
size (C) to confirm the number of mobile cameras that havenot been assigned a transmission order. Because size (C) is
0, the access point terminates the transmission order control
algorithm. Thus, the final transmission order is mobile camera
1 → mobile camera 3 → mobile camera 2.
D. Encoding
When each mobile camera receives the transmission orderfrom the access point, it encodes its own video according to
the transmission order. Each mobile camera encodes the 1GOP video based on H.264/AVC.
Each mobile camera overhears the communication from allother cameras, thus enabling a reduction in video traffic. Figure
4 shows the prediction structure of MVS/MC. This prediction
structure assumes that the number of mobile cameras, theirposition, and the transmission order are the same as in Figure
3. Figure 4(a) shows the prediction structure of mobile camera
1. The anchor frame of the structure is encoded using an Iframe, which is a picture that is encoded independently of theother pictures.

Globecom 2014 - Communications Software, Services and Multimedia Symposium

time

time

1

I

B

B

B

B

B

B

1

3

Mobile camera

I

B

P

B

B

B

B

B

B

B

B

B

B

B

Mobile camera

time

1

I

B

B

B

B

B

B

2

B

B

B

B

B

B

B

3

P

B

B

B

B

B

B

Mobile camera(a) Prediction structure of mobile camera 1 (b) Prediction structure of mobile camera 3 (c) Prediction structure of mobile camera 2
Fig. 4.

MVS/MC’s prediction structure

Access point

Mobile camera1

Mobile camera2

Mobile camera3

Fig. 5.

order1

P1,1

(1)

EoG

P3,1

EoG

P2,1

P1, 2

EoG

order2

EoG

order2

P 1,2

EoG

EoG

order2

P1,2

EoG

EoG

order2

P1,2

EoG

(5)

(2)

order1

P 1,1

EoG

order1

P1,1

EoG

P3,1

order1

P1,1

EoG

P 3,1

EoG

EoG

(6)

(4)
EoG

P 2,1

(3)
EoG

Timing diagram of MVS/MC

3)

Figure 4(b) shows the prediction structure of mobile camera 3. This camera encodes its own video using the overheard
video from camera 1. The anchor frame of camera 3’s video is
encoded using a P-frame, which encodes only the differencesfrom camera 1’s I-frame, and thus requires less bandwidth thanthe I-frame.
Figure 4(c) shows the prediction structure of mobile camera
2. Mobile camera 2 encodes its own video using the overheard
video from cameras 1 and 3. The anchor frame of camera
2’s video is encoded as a B-frame. B-frames encode thedifferences based on both camera 1’s I-frame and camera 3’s
P-frame, and thus require less bandwidth than the P-frame.

4)5)

E. Video transmission
Each mobile camera transmits its own encoded video to anaccess point according to the transmission order determinedby the access point.
Figure 5 shows the timing diagram of MVS/MC. Figure 5
assumes that the transmission order determined by the accesspoint is mobile camera 1 → mobile camera 3 → mobile camera
2. Pi,j represents the video packet of mobile camera i in GOP
j.
1)
2)

The access point broadcasts the transmission orderfor GOP 1 to all mobile cameras.
When the mobile cameras receive the transmission
order, mobile camera 1 starts video transmission.
Mobile camera 1 transmits P1,1 to the access point.
P1,1 includes position information about camera 1
in the position field and the encoded video in thevideo field. Mobile cameras 2 and 3 overhear P1,1

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6)

and decode the video. After P1,1 has been transmitted, mobile camera 1 broadcasts an End-of-GOP(EoG) packet. The EoG packet informs other mobile
cameras about the end of 1-GOP video transmission.
The format of the EoG packet is the same as that ofan ACK frame in IEEE 802.11 [23]. When mobile
camera 3 overhears the EoG packet, it encodes its
own video with the video overheard from camera 1,
and commences video transmission. Mobile camera 2
stores camera 1’s video, and waits for an EoG packet
from mobile camera 3.
Mobile camera 3 transmits P3,1 to the access point.
P3,1 includes camera 3’s position information in theposition field and the encoded video in the video
field. Mobile camera 2 overhears P3,1 and decodes
the video. After P3,1 has been transmitted, mobile
camera 3 broadcasts an EoG packet. When mobile
camera 2 overhears the EoG packet, mobile camera
2 encodes its own video using the videos overheard
from cameras 1 and 3. Mobile camera 2 then commences video transmission.
Mobile camera 2 transmits P2,1 to the access point.
P2,1 includes camera 2’s position information in theposition field and the encoded video in the video
field. After P2,1 has been transmitted, mobile camera
2 broadcasts an EoG packet.
When the access point receives the EoG packet frommobile camera 2, it transmits P1,1 , P2,1 , and P3,1 toan encoder. After this transmission, the access point
determines the transmission order for the second GOP
based on the position information included in P1,1 ,P2,1 , and P3,1 . The transmission order for the second
GOP is then broadcast to all mobile cameras.
Mobile camera 1 transmits P1,2 to the access point.
Mobile cameras 2 and 3 overhear P1,2 and decodethe video. After P1,2 has been transmitted, mobile
camera 1 broadcasts an EoG packet.

MVS/MC repeats (2) to (6) until the end of video transmission
for all GOPs.
F. Decoding
MVS/MC does not require a special decoder. Each mobile
camera and the encoder exploit a standard H.264/AVC video
decoder. The mobile cameras and the encoder first receive anddecode the I-frame. The video frames received by the mobileGlobecom 2014 - Communications Software, Services and Multimedia Symposium

Traffic [Mbit/video]

4

TABLE II.
Independent Streaming
MVC/MC

Resolution
Frame rate
Number of frames
GOP size
Number of mobile cameras
Quantization parameter (QP)

3
2

32

34

36

38

PSNR [dB]2)

Independent Streaming
MVC/MC w/o order control
MVC/MC

3)

PSNR vs. Traffic

Traffic [Mbit/video]

4
3
2

32

34

36

We compared the volume of traffic required for different
levels of video quality. This evaluates the baseline performanceof traffic reduction while maintaining high video quality for thethree encoding/decoding schemes described in Section IV-A.
We use the standard peak signal-to-noise ratio (PSNR) metricto evaluate the video quality. The PSNR represents the video
quality of multi-view video as follows:

38

PSNR [dB]
PSNR vs. Traffic with different camera positions

cameras and the encoder are then encoded using the previously
received video frames. The mobile cameras and the encoder
decode the newly received video after decoding the previously
received video. When the encoder decodes video frames fromall mobile cameras, the video frames are encoded based ona multi-view video coding technique, such as MVC, IMVS,
or UDMVT. Finally, the encoder transmits the encoded video
frames to a user’s device. The user can then play back themulti-view video.
IV.

E VALUATION

A. Evaluation settings
To evaluate the traffic and video quality of MVS/MC, we
implemented a MVS/MC encoder/decoder with JMVC, which
is an open source project [24]. The distance between themobile cameras in these video sequences is 19.5 [cm]. These
test video sequences are provided by MERL [25]. Table IIshows the encoding parameters of the evaluation. Evaluation
settings are as follows: the resolution is 176×144, the frame
rate is 15 fps, number of frames is 250, GOP size is 8, numberof mobile cameras is 8 and quantization parameter is 24-40.

(
P SN R = 20 log10

Independent Streaming
Independent Streaming encodes the video of each
mobile camera independently, and transmits the video
to the access point. Independent Streaming gives the

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M AX
√
M SE

)

where MAX is the largest pixel value and MSE is the meansquared error between all pixels of the decoded and originalvideos.
We implemented Independent Streaming and MVS/MC on
the JMVC encoder. This evaluation used the Ballroom video
sequence, and we assumed that the position of each mobile
camera was fixed. The JMVC encoder encodes the video
frames of a mobile camera with or without the video framesof other mobile cameras, depending on the encoding/decoding
scheme. The video frames were encoded using different QP
values to evaluate the effect on traffic volume and video
quality. When QP is large, the traffic volume and quality ofthe video frames are low. Finally, the JMVC encoder calculates
the average traffic volume for each PSNR.
Figure 6 shows the traffic produced by each encoding/decoding scheme as a function of PSNR. Figure 6 shows
the following:1)

We evaluate the traffic and video quality of three encoding/decoding schemes: Independent Streaming, MVS/MC w/otransmission order control, and MVS/MC.
1)baseline performance, using the simplest method for
multi-view video acquisition with wireless networks.
MVS/MC w/o order control
MVS/MC w/o transmission order control supports
only the packet overhearing technique of MVS/MC.
Even when the position of a mobile camera changes,
each mobile camera transmits its own encoded video
in the previously assigned order.
MVS/MCAs described in Section III, MVS/MC is the proposed
approach. MVS/MC supports both overhearing andtransmission order control.

B. PSNR vs. Traffic

10Fig. 7.

176×144
15 fps250
8 frames
8
24-40

1
0

Fig. 6.

E VALUATION SETTINGS

2)

MVS/MC reduces traffic compared to Independent
Streaming for the same video quality. For example,
when the PSNR is 36 [dB], MVS/MC reduces traffic
by 700 [Kbits/video] compared with Independent
Streaming. This is because MVS/MC removes redundant information using the overheard video fromother mobile cameras.
As PSNR increases, the difference between the traffic volume produced by MVS/MC and IndependentGlobecom 2014 - Communications Software, Services and Multimedia Symposium

Streaming becomes larger. For example, when the
PSNR is 32 [dB], MVS/MC reduces traffic by 240[Kbits/video] compared with Independent Streaming,
but when the PSNR is 39 [dB], MVS/MC reduces
traffic by 980 [Kbits/video]. When the PSNR ishigh, the video traffic increases because the videofrom each mobile camera is similar to the originalvideo. As a result, the traffic produced by Independent Streaming increases greatly with an increase in
PSNR. The volume of redundant video information
increases when the video from each mobile camera
is almost the same as the original. MVS/MC exploits
this redundant information during the encoding process, thus achieving a considerable reduction in traffic
volume.

R EFERENCES
[1]

[2]

[3]

[4]
[5]

[6]
[7]

C. Effect of transmission order control
Sections IV-Bdiscussed the performance of MVS/MC withpacket overhearing and transmission order control. This section
evaluates the contribution of packet overhearing and transmission order control in more detail by comparing the traffic
volume using MVS/MC to that of MVS/MC w/o transmission
order control.

[8]

[9]
[10]

As in the evaluation in Section IV-B, we implemented thethree encoding/decoding schemes on the JMVC encoder. To
evaluate the effect of transmission order control, we randomly
exchanged the positions of the mobile cameras, and evaluatedthe average traffic of the three encoding/decoding schemes over
100 evaluations.

[11]

Figure 7 shows the traffic produced by each encoding/decoding scheme as a function of PSNR. From this, we
can conclude the following:

[14]

[12]
[13]

[15]

1)

2)

MVS/MC achieves the lowest traffic of the three
encoding/decoding schemes, even when the positionof each mobile camera is changed. For example,
MVS/MC reduces traffic by 700 [Kbits/video] compared to MVS/MC w/o transmission order control.
The difference in traffic volume between MVS/MC
w/o order control and Independent Streaming is relatively small. This is because there is little redundant
information among the mobile cameras when theirpositions are changed and the transmission order isfixed. This shows that the transmission order control
gives a strong advantage in achieving low video
traffic and high video quality.

[16]
[17]

[18]
[19]

[20]
[21]

[22]

V.

C ONCLUSION

This paper proposed Multi-view Video Streaming with
Mobile Cameras (MVS/MC) for multi-view video acquisition
over wireless networks. MVS/MC achieves a reduction intraffic volume while maintaining high video quality by meansof packet overhearing and transmission order control. Througha series of evaluations, it was revealed that MVS/MC enables
low traffic volumes with only a small degradation in video
quality.

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