Tao Fang

Bio: Tao Fang is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Video quality & Scalable Video Coding. The author has an hindex of 4, co-authored 14 publications receiving 156 citations.

GOP-based channel rate allocation using genetic algorithm for scalable video streaming over error-prone networks

Abstract: In this paper, we address the problem of unequal error protection (UEP) for scalable video transmission over wireless packet-erasure channel. Unequal amounts of protection are allocated to the different frames (I- or P-frame) of a group-of-pictures (GOP), and in each frame, unequal amounts of protection are allocated to the progressive bit-stream of scalable video to provide a graceful degradation of video quality as packet loss rate varies. We use a genetic algorithm (GA) to quickly get the allocation pattern, which is hard to get with other conventional methods, like hill-climbing method. Theoretical analysis and experimental results both demonstrate the advantage of the proposed algorithm.

A novel unequal error protection approach for error resilient video transmission

Abstract: We address the problem of unequal error protection (UEP) for MPEG-2/H.263 video over a wireless packet-erasure channel. Unequal amounts of protection are allocated to the different frames of a group-of-pictures (GOP) to provide a graceful degradation of video quality as packet loss rate varies. We use a genetic algorithm (GA) to get the allocation pattern quickly. Theoretical analysis and experimental results both demonstrate the advantages of the proposed algorithm.

Two-Dimensional Channel Coding Scheme for MCTF-Based Scalable Video Coding

Abstract: The motion-compensated temporal filtering (MCTF)-based scalable video coding (SVC) provides a full scalability including spatial, temporal and signal-to-noise ratio (SNR) scalability with fine granularity, each of which may result in different visual effect. This paper addresses a novel approach of two-dimensional unequal error protection (2D UEP) for the scalable video with a combined temporal and quality (SNR) scalability over packet-erasure channel. The bit-stream is divided into scalable subbitstreams based on the structure of MCTF. Each subbitstream is further divided into several quality layers. Unequal quantities of bits are allocated to protect different layers to obtain acceptable quality video with smooth degradation under different transmission error conditions. Experimental results are presented to show the advantage of the proposed 2D UEP scheme over the traditional one-dimensional unequal error protection (1D UEP) scheme. Comparing the proposed method with the 1D UEP scheme on SNR layers, our method gives up to 0.81-dB improvement for some video sequences

An error-resilient GOP structure for robust video transmission

Abstract: Recent advances in technology have resulted in a significant growth in wireless communications and widespread access to information via the Internet, which have resulted in a strong demand for reliable transmission of video data. The challenge of robust video transmission is to protect the compressed data against hostile channel conditions while bringing little impact on bandwidth efficiency. In motion-compensated video-coding schemes, such as MPEG-1 or MPEG-2, an I frame normally is followed by several P frames and possibly B frames in a group-of-pictures (GOP). In error-prone environments, error happening in the previous frames in a GOP may propagate to all the following frames until the next I frame, which is the beginning of the next GOP. In this paper, we propose a novel GOP structure for robust transmission of MPEG video bitstream. By selecting the optimal position of the I frame in a GOP, robustness can be achieved without reducing any coding efficiency. Another advantage of the proposed GOP structure is also analyzed: compared with the conventional GOP structure, it provides reverse-play operation for MPEG video streaming with much less requirement on the network bandwidth. Experimental results demonstrate both the robustness of the proposed GOP structure and the efficient reverse-play functionality it leads to.

Efficient content-based resynchronization approach for wireless video

Abstract: Recent advances in technology have caused a significant growth in wireless communications, which have resulted in a strong demand for reliable transmission of video data. The challenge of robust video transmission is to protect the compressed data against hostile channel conditions while bringing little impact on bandwidth efficiency. In this paper, using results from a simplified macroblock-based segmentation algorithm, we propose a framework called content-based resynchronization for the effective positioning of resynchronization markers such that the image quality of foreground can be improved at the expense of sacrificing unimportant background. We do this because, in applications such as video telephony and video conferencing, foreground is typically the most important image region for viewers. Experimental results demonstrate that this scheme significantly improve the perceptual quality of video sequences for robust video transmission.

Genetic algorithms in wireless networking: techniques, applications, and issues

Abstract: In recent times, wireless access technology is becoming increasingly commonplace due to the ease of operation and installation of untethered wireless media. The design of wireless networking is challenging due to the highly dynamic environmental condition that makes parameter optimization a complex task. Due to the dynamic, and often unknown, operating conditions, modern wireless networking standards increasingly rely on machine learning and artificial intelligence algorithms. Genetic algorithms (GAs) provide a well-established framework for implementing artificial intelligence tasks such as classification, learning, and optimization. GAs are well known for their remarkable generality and versatility and have been applied in a wide variety of settings in wireless networks. In this paper, we provide a comprehensive survey of the applications of GAs in wireless networks. We provide both an exposition of common GA models and configuration and provide a broad-ranging survey of GA techniques in wireless networks. We also point out open research issues and define potential future work. While various surveys on GAs exist in the literature, our paper is the first paper, to the best of our knowledge, which focuses on their application in wireless networks.

Unequal Error Protection for Robust Streaming of Scalable Video Over Packet Lossy Networks

Abstract: Efficient bit stream adaptation and resilience to packet losses are two critical requirements in scalable video coding for transmission over packet-lossy networks. Various scalable layers have highly distinct importance, measured by their contribution to the overall video quality. This distinction is especially more significant in the scalable H.264/advanced video coding (AVC) video, due to the employed prediction hierarchy and the drift propagation when quality refinements are missing. Therefore, efficient bit stream adaptation and unequal protection of these layers are of special interest in the scalable H.264/AVC video. This paper proposes an algorithm to accurately estimate the overall distortion of decoder reconstructed frames due to enhancement layer truncation, drift/error propagation, and error concealment in the scalable H.264/AVC video. The method recursively computes the total decoder expected distortion at the picture-level for each layer in the prediction hierarchy. This ensures low computational cost since it bypasses highly complex pixel-level motion compensation operations. Simulation results show an accurate distortion estimation at various channel loss rates. The estimate is further integrated into a cross-layer optimization framework for optimized bit extraction and content-aware channel rate allocation. Experimental results demonstrate that precise distortion estimation enables our proposed transmission system to achieve a significantly higher average video peak signal-to-noise ratio compared to a conventional content independent system.

Layer-weighted unequal error protection for scalable video coding extension of H.264/AVC

Abstract: The scalable video coding extension of H.264/AVC is a current standardization project. This paper deals with unequal error protection (UEP) scheme for scalable video bitstream over packet-lossy networks using forward error correction (FEC). The proposed UEP scheme is developed by exploiting jointly the unequal importance existing both in temporal layers and quality layers of hierarchial scalable video bitstream. For efficient assignment of FEC codes, the proposed UEP scheme uses a simple and efficient performance metric, namely layer-weighted expected zone of error propagation (LW-EZEP). The LW-EZEP is adopted for quantifying the error propagation effect on video quality degradation from packet loss in temporal layers and in quality layers. Compared to other UEP schemes, the proposed UEP scheme demonstrates strong robustness and adaptation for variable channel status.

GOP-based channel rate allocation using genetic algorithm for scalable video streaming over error-prone networks

Abstract: In this paper, we address the problem of unequal error protection (UEP) for scalable video transmission over wireless packet-erasure channel. Unequal amounts of protection are allocated to the different frames (I- or P-frame) of a group-of-pictures (GOP), and in each frame, unequal amounts of protection are allocated to the progressive bit-stream of scalable video to provide a graceful degradation of video quality as packet loss rate varies. We use a genetic algorithm (GA) to quickly get the allocation pattern, which is hard to get with other conventional methods, like hill-climbing method. Theoretical analysis and experimental results both demonstrate the advantage of the proposed algorithm.

Optimal Video Streaming in Dense 5G Networks With D2D Communications

Abstract: Mobile video traffic and mobile devices have now outpaced other data traffic and fixed devices. Global service providers are attempting to propose new mobile infrastructures and solutions for high performance of video streaming services, i.e., high quality of experience (QoE) at high resource efficiency. Although device-to-device (D2D) communications have been an emerging technique that is anticipated to provide a massive number of mobile users with advanced services in 5G networks, the management of resource and co-channel interference between D2D pairs, i.e., helper-requester pairs, and cellular users (CUs) is challenging. In this paper, we design an optimal rate allocation and description distribution for high performance video streaming, particularly, achieving high QoE at high energy efficiency while limiting co-channel interference over D2D communications in 5G networks. To this end, we allocate optimal encoding rates to different layers of a video segment and then packetize the video segment into multiple descriptions with embedded forward error correction before transmission. Simultaneously, the optimal numbers of descriptions are distributed to D2D helpers and base stations in a cooperative scheme for transmitting to the D2D requesters. The optimal results are efficiently in correspondence with intra-popularity of different segments of a video characterized by requesters’ behavior, characteristic of lossy wireless channels, channel state information of D2D requesters, and constraints on remaining energy of D2D helpers and target signal to interference plus noise ratio of CUs. Simulation results demonstrate the benefits of our proposed solution in terms of high performance video streaming.