nils-herrmann/clean_scirepeval huggingface dataset:
Uniform threshold TCQ with block classification for image transmission over noisy channels

A combined source-channel coding scheme without explicit error protection is proposed to transmit images over noisy channels. Major components of the proposed coding scheme include 2-D DCT with block classification, fixed-length uniform threshold trellis coded quantization, optimal bit-allocation algorithm, and noise reduction filters. The integration of these components allows us to organize the compressed bitstream in such a way that it is less sensitive to channel noise, and hence achieves data compression and error resilience at the same time. This paper reports our previous study by incorporating the block classification into the integrated scheme. Experimental results show that, in the case of noise-free channels and at the bit rate of 0.5 bpp, an improvement of 2.33 dB can be achieved with the classification. In the case of noisy channels, the gain decreases as the bit error rate increases. However, we can still achieve an average improvement of 0.46 dB, even for highly noisy channels with BER=0.1. Our proposed system uses no error protection, no synchronization codewords and no entropy coding. However, it shows a decent compression ratio and graceful degradation with respect to increasing channel errors.
Constant Quality Aimed Bit Allocation for 3D Wavelet Based Video Coding

MCTF has been widely used in wavelet based video coding due to its attractive features. For MCTF based codecs, a fundamental question is how to allocate bits to each temporal band so that certain degree of constant quality can be achieved. In this paper, we propose a novel approach for constant quality aimed bit allocation among T-bands for the applications of adaptive stored video streaming. The basic idea of our proposed scheme is to adjust the energy gains based on an empirical model to compensate the different contributions from different types of T-bands, and more or less equally distribute the distortions among the T-bands at the same level. Experimental results show that our proposed bit allocation can greatly reduce the PSNR fluctuation with only slight degradation in average PSNR
Scalable Video Transmission over the IEEE 802.11e Networks Using Cross-Layer Rate Control

This paper presents a novel cross-layer rate control scheme for optimizing 3D wavelet scalable video transmission over the IEEE 802.11e wireless local area networks. The proposed scheme consists of a macro and a micro rate control schemes residing at the application layer and the network sublayer respectively. The macro rate control uses bandwidth estimation to achieve optimal bit allocation with minimum distortion. The micro rate control employs an adaptive mapping of packets using video classifications. This prioritizes appropriately the video traffic to maximize the transmission protection to the important video packets. The performance is investigated by simulations showing advantages of our cross-layer design.
WLC19-6: Capacity Analysis of Supporting VoIP in IEEE 802.11e EDCA WLANs

Directly implementing voice over Internet protocol (VoIP) over infrastructure wireless local area networks (WLANs) will have the bottleneck problem in the access point (AP). In this paper, we propose to use the service differentiation provided by the new IEEE 802.11e standard to solve the bottleneck problem and improve the voice capacity. In particular, we propose to allocate higher priority access category (AC) to the AP while allocating lower priority AC to mobile stations. We develop a simple Markov chain model, which considers not only the important enhanced distributed channel access (EDCA) parameters but also the channel errors. Based on the developed analytical model, we analyze the performance of VoIP over EDCA. Through appropriately selecting the EDCA parameters, we are able to differentiate the services for the downlink and the uplink. The experimental results are very promising: with the adjustment of only one EDCA parameter, we improve the VoIP capacity by 20~30%.
Converting 2D soccer video to 3D cartoon

Video-to-cartoon is a promising technology for mobile applications. In this paper, we develop a video-to-cartoon system, which can analyze video content and generate the corresponding 3D cartoon. The proposed system consists of two major parts: the media analysis module and the cartoon rendering module, where the former is to extract the 3D information from 2D video and the latter is to roughly reconstruct the 3D scene using the pre-generated models and animations and the extracted 3D information. Compared with the existing video-to-cartoon systems, our developed system generates 3D cartoon instead of 2D cartoon, supports interaction and is able to render the 3D cartoon in a fast manner.
Complexity-rate-distortion evaluation of video encoding for cloud media computing

Cloud computing provides a promising solution to cope with the increased complexity in new video compression standards and the increased data volume in video source. It not only saves the cost of too frequent equipment upgrading but also gives individual users the flexibilities to choose the amount of computing according to their needs. To facilitate cloud computing for real-time video encoding, in this paper we evaluate the amount of computing resource needed for H.264 and H.264 SVC encoding. We focus on evaluating the complexity-rate-distortion (C-R-D) relationship with a fixed encoding process but under different external configuration parameters. We believe such an empirical study is meaningful for eventually realizing real-time video encoding in an optimal way in a cloud environment.
Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval

In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.
Admission control with physical rate measurement for IEEE 802.11e controlled channel access

A simple admission control unit has already been developed as a reference for HCF (hybrid coordination function) controlled channel access (HCCA) in a recent 802.11e draft. However, this reference scheme is inefficient because it is implemented based on the minimum physical rate from which the mobile stations' actual physical rates deviate greatly at most of the time. In this letter, we propose a physical rate based admission control scheme (PRBAC) which enhances the reference scheme by taking account of both of the wireless channel characteristics and the stations' mobility. Simulation results show the significant improvement of the proposed admission control scheme.
Optimizing content retrieval delay for LT-based distributed cloud storage systems

Among different setups of cloud storage systems, fountain-codes based distributed cloud storage system provides reliable online storage solution through placing coded content fragments into multiple storage nodes. Luby Transform (LT) code is one of the popular fountain codes for storage systems due to its efficient recovery. However, to ensure high success decoding of fountain codes based storage, retrieval of additional fragments is required, and this requirement introduces additional delay, which is critical for content retrieval or downloading applications. In this paper, we show that multiple-stage retrieval of fragments is effective to reduce the content-retrieval delay. We first develop a delay model for various multiple-stage retrieval schemes applicable to our considered system. With the developed model, we study optimal retrieval schemes given the success decodability requirement. Our numerical results demonstrate that the content-retrieval delay can be significantly reduced by optimally scheduling packet requests in a multi-stage fashion.
Message from ICME'12 Technical Program Chairs

ICME has been a flagship international conference for the presentation of novel and fundamental research advances in the field of Multimedia since 2000. It is sponsored by four IEEE societies ( Circuit and System Society and IEEE Computer Society), and ICME 2012 is the 13th event. During the main conference (Jul. 10-12, 2012), the ICME 2012 daily technical program will start with a keynote talk delivered by a world class scientist. At the end of the keynote, a number of papers which are best paper award candidates will be highlighted. Four parallel oral sessions will be presented in the morning, and four additional parallel oral sessions will be presented in the early afternoon. Then, a research overview plenary session will run right after the afternoon tea break. We have designed the program in such a way that ICME audience will not miss the keynotes, overview talks and the plenary session, and can always find a high quality talk of interest at the parallel oral sessions. In addition, a 1.5 ~ 2 hour session is held in each afternoon with poster presentations and demos. Each oral paper is also provided with an additional poster presentation slot so that authors can have ample opportunity to interact with audience. ICME 2012 will give five awards including the best paper award, the best paper runner-up award, the best student paper award, the best student paper runner up award and the best demo award. we are pleased to report a strong technical program with exceptional quality.  Lead by 6 Program Chairs and 18 Track Chairs, we have conducted the paper review in a double-blind manner with several aspects aimed to achieve a very rigorous review process, including author rebuttal, review discussion, meta-review and within-track discussions and cross-track discussions. Almost all papers have received 3 independent reviews, with 78% of the paper receiving 4 or more reviews. These reviews served as basis to select the 184 papers accepted into the main conference, a 30% overall acceptance rate. Out of the 184 accepted papers, top review scores papers are selected for oral presentation. In particular, the oral paper sessions consist of 79 accepted papers and 9 special session papers, corresponding to a 13% (14.4% if including special session papers) accepance rate. A selected set of high quality ICME 2012 papers will also be invited to submit an extended version of the paper to be reviewed for acceptance into a special issue of
An adaptive multi-layer low-latency transmission scheme for H.264 based screen sharing system

Virtual screen system is becoming an essential part in the mobile cloud computing platform. However, designing a low-latency interactive communication for the high-resolution screen content is still challenging due to the network dynamics and the unique characteristics of screen content. In this paper we propose a H.264 based low-latency screen sharing system. To achieve high play-out frame rate, we decouple the low-latency screen content communication problem into two parts, a scalable H.264 based encoding and an optimal scalable stream transmission scheduling. By leveraging the unique characteristics of screen content, a multi-layer scalable video encoding scheme is designed to achieve a certain error resilience while keeping good video coding efficiency. In the transmission scheduling module, an optimal frame skipping policy is proposed to schedule the frames in the buffer to maximize the play-out frame rate. In the performance evaluation, we simulate our system in both one-hop end-to-end topology and two-hop proxy-based topology. The simulation results show that the proposed scheme achieves much better performance on frame rate and average delay, especially in the low bandwidth condition.
Content-Based Image Compression for Arbitrary-Resolution Display Devices

The work presented in this paper addresses the increasing demand of visual signal delivery to terminals with arbitrary resolutions (like in mobile multimedia communication and cloud computing) for universal access and presentation, without extra computational burden to the receiving end. Scalable image compression and transmission are essential, and to be effective and meaningful, it has to be content-based. The existing coding methods cannot support content-based spatial scalability with high compression. In this paper, the principle of seam carving (SC) is incorporated into a wavelet codec. After multi-level discrete wavelet transform (DWT), SC is performed in the low frequency subband. Different from the conventional wavelet-based coding schemes, DWT coefficients here are encoded and transmitted according to the energy map of resultant seams. At the decoder side, the end user has the ultimate choice for the scalability without the need to examine the visual content; an image with arbitrary aspect ratio can be reconstructed in a content-aware manner based upon the encoded information. Simulation results show that the resized images preserve important content while achieving high coding efficiency in transmission.
Scalable multiview video coding using wavelet

In this paper, we propose a multiview video coding (MVC) scheme based on wavelets which can provide temporal, spatial, SNR as well as view scalabilities. To the best of our knowledge, wavelets have not been used for MVC in the literature before. In particular, we consider a multiview video as a 2D matrix with 1D along the temporal axis, 1D along the view axis, and each element in the 2D matrix represents a video frame. We first apply 1D wavelet decomposition to the 2D matrix along the temporal axis with motion compensation, and then along the view axis with disparity compensation. After that, 2D spatial wavelet decomposition is applied to each element in the matrix. Finally, all the subbands are encoded by 3D-ESCOT with rate-distortion optimization. Compared with traditional 3D wavelet coding, our proposed wavelet-based MVC scheme applies one more dimensional wavelet transform along the view direction to exploit the redundancy between adjacent views. Some preliminary experiments are carried out using standard multiview video sequences and the efficiency of the proposed system is confirmed.
DC-MAC: A data-centric multi-hop MAC protocol for underwater acoustic sensor networks

Due to the unique characteristics of long signal propagation, high error rate and low bandwidth in the underwater environment, the design of the medium access control (MAC) protocol for underwater acoustic networks poses significant challenges. The previous MAC protocols designed for flexible communication models have limited achievements in performance. In this paper, we consider a practical application and propose a data-centric multi-hop MAC protocol, called DC-MAC, to enhance the performance on throughput and average end-to-end packet transmission delay. Our design uses multi-channel strategy to limit transmission interference by creating multiple collision domains, and dynamic collision-free polling strategy to offer efficient protocol handshake. We analyze the saturation throughput performance and conduct extensive simulation experiments to study the throughput and delay performance. Comparing to slotted FAMA which is a potential MAC protocol candidate for the same environment, our results show that DC-MAC outperforms its peer.
Image Co-segmentation via Saliency Co-fusion

Most existing high-performance co-segmentation algorithms are usually complex due to the way of co-labeling a set of images as well as the common need of fine-tuning few parameters for effective co-segmentation. In this paper, instead of following the conventional way of co-labeling multiple images, we propose to first exploit inter-image information through co-saliency, and then perform single-image segmentation on each individual image. To make the system robust and to avoid heavy dependence on one single saliency extraction method, we propose to apply multiple existing saliency extraction methods on each image to obtain diverse salient maps. Our major contribution lies in the proposed method that fuses the obtained diverse saliency maps by exploiting the inter-image information, which we call saliency co-fusion. Experiments on five benchmark datasets with eight saliency extraction methods show that our saliency co-fusion-based approach achieves competitive performance even without parameter fine-tuning when compared with the state-of-the-art methods.
Optimal Frame Selection with Adaptive Playout for Delivering Stored Video under Constrained Resources

In this paper, we propose a server-client coordinated joint optimal frame selection with adaptive playout for delivering stored video under both limited channel bandwidth and finite client buffer condition. In particular, the client will reduce the frame playout rate whenever its buffer fullness level falls below a given threshold in an attempt to prevent buffer underflow. And when the buffer fullness exceeds the threshold, the client will switch back to the normal frame playout rate. The server is aware of the adaptive playout decision made by the client and incorporates the decision into its optimal frame selection framework for joint optimization. The objective is to minimize the number of frames that must be discarded in order to prevent client buffer underflow or overflow and make full use of the limited bandwidth resource.
vCache: Supporting Cost-Efficient Adaptive Bitrate Streaming via NFV-Based Virtual Caching

Adaptive bitrate (ABR) streaming is widely adopted to tackle the diversity of user devices and varying network conditions. With ABR, each video must be transcoded into multiple representations in different bitrates and resolutions. It consumes tremendous resources for transcoding and caching videos, yet only a small percentage of video chunks are frequently requested. This raises the question: is it necessary to pre-transcode each video and keep the video chunks of all representations in storage? To answer it, we design a NFV-based virtual cache (vCache) for ABR. In vCache, video chunks have two mutually-exclusive caching states: physically cached or virtually cached. A physically cached video chunk can be read from storage directly, and it consumes storage resources. A virtually cached video chunk will be transcoded on the fly when being requested, and it consumes computing resources. Leveraging NFV infrastructure, vCache can dynamically manages the caching states of each video chunk to achieve overall cost-efficiency, and dynamically provision computing resources for transcoding to guarantee transcoding delays are within an acceptable range. Experiment results demonstrate that vCache can greatly reduce the operational cost for ABR.
An FEC-based error control scheme for wireless MPEG-4 video transmission

In this paper, we propose an FEC-based error control scheme for the transmission of low bit rate MPEG-4 video over wireless channels. The proposed error control scheme, through integrating with MPEG-4 inherent error resilient techniques, divides the MPEG-4 bitstream into several classes. Such division of the bitstream not only facilitates unequal error protection for different classes of data but also allows local reorganization of the bitstream into a fixed-length structure. This reorganization enables robust decoding at the receiving end, however, results in little side information and causes negligible delay. The proposed scheme can also be combined with motion-compensation based error concealment for effective post processing. Experimental results demonstrate that the performance of the proposed scheme is much better than that of the simple equal error protection scheme, not only in PSNR but also in visual quality, in terms of the reconstructed video frames at the receiver.
Inter-screen interaction for session recognition and transfer based on cloud centric media network

Recently, there is a growing trend that people tend to consume media over multi-screens simultaneously. This paper proposes an efficient and convenient inter-screen interaction approach based on our cloud centric media network, where all the ongoing sessions on the client side are always synchronized with the media cloud. This approach realizes the session recognition and transfer over different devices in a three-step manner. First, the users are required to use the mobile device camera to scan the main screen. Second, after the screen edge detection and image correction, users are allowed to choose one or more ongoing session on the corrected image via touch screen to request the transfer. Finally, the selected sessions are identified by the cloud, and those sessions are delivered to the mobile devices to complete the session transfer. The algorithms and strategies involved are discussed in detail. We also implement a testbed on top of a private cloud at NTU. The results prove our proposed method is robust and easy to use.
QoS-Aware Resource Allocation for Video Transcoding in Clouds

As the biggest big data, video data streaming in the network contributes the largest portion of global traffic nowadays and in the future. Due to heterogeneous mobile devices, networks, and user preferences, the demands of transcoding source videos into different versions have increased significantly. However, video transcoding is a time-consuming task, and how to guarantee quality-of-service (QoS) for large video data is very challenging, particularly for those real-time applications that hold strict delay requirement such as live TV. In this paper, we propose a cloud-based online video transcoding (COVT) system aiming to offer economical and QoS guaranteed solution for online large-volume video transcoding. COVT utilizes the performance profiling technique to obtain the different performances of transcoding tasks in different infrastructures. Based on the profiles, we model the cloud-based transcoding system as a queue and derive the QoS values of the system based on the queuing theory. With the analytically derived relationship between QoS values and the number of CPU cores required for transcoding workloads, COVT is able to solve the optimization problem and obtain the minimum resource reservation for specific QoS constraints. A task scheduling algorithm is further developed to dynamically adjust the resource reservation and schedule the tasks so as to guarantee the QoS in runtime. We implement a prototype system of COVT and experimentally study the performance on real-world workloads. Experimental results show that the COVT effectively provisions a minimum number of resources for predefined QoS. To validate the effectiveness of our proposed method under large-scale video data, we further perform simulation evaluation, which again shows that the COVT is capable of achieving economical and QoS-aware video transcoding in cloud environment.