Videoconferencing is an important global application-it enables people around the globe to interact when distance separates them. In order for the participants in a videoconference call to interact naturally, the end-to-end delay should be below human perception; even though an objective and unique figure cannot be set, 100 ms is widely recognized as the desired one-way delay requirement for interaction. Since the global propagation delay can be about 100 ms, the actual end-to-end delay budget available to the system designer (excluding propagation delay) can be no more than 10 ms. We identify the components of the end-to-end delay in various configurations with the objective of understanding how it can be kept below the desired 10-ms bound. We analyze these components step-by-step through six system configurations obtained by combining three generic network architectures with two video encoding schemes. We study the transmission of raw video and variable bit rate (VBR) MPEG video encoding over (1) circuit switching; (2) synchronous packet switching; and (3) asynchronous packet switching. In addition, we show that constant bit rate (CBR) MPEG encoding delivers unacceptable delay-on the order of the group of pictures (GOP) time interval-when maximizing the quality for static scenes. This study aims at showing that having a global common time reference, together with time-driven priority (TDP) and VBR MPEG video encoding, provides adequate end-to-end delay, which is (1) below 10 ms; (2) independent of the network instant load; and (3) independent of the connection rate. The resulting end-to-end delay (excluding propagation delay) can be smaller than the video frame period, which is better than what can be obtained with circuit switching.

End-to-end delay analysis of videoconferencing over packet-switched networks

This paper presents a joint coding scheme for multiprogram video transmission. By exploiting the statistical variations of the program content, the joint coding achieves a more optimal bit allocation, which results in a better and more uniform picture quality. The bit allocation strategy assigns the same quantization parameter to all the programs, and the rate control adjusts this quantization parameter from frame to frame so that the aggregate bit rate for the programs is within a given bit budget. The programs are coded using the MPEG-2 video coding standard which inherently generates a variable rate bit stream.

Joint rate control for multi-program video coding

Rate control (RC) plays a critical role in the transmission of high-quality video data under certain bandwidth restrictions in High Efficiency Video Coding (HEVC). Most current HEVC RC algorithms based on spatio-temporal information for rate-distortion (R-D) model parameters cannot effectively handle the cases with dynamic video sequences that contain fast moving objects, significant object occlusion or scene changes. In this paper, we propose an RC method based on deep reinforcement learning (DRL) for dynamic video sequences in HEVC to improve the coding efficiency. First, the rate control problem is formulated as a Markov decision process (MDP) problem. Second, with the MDP model, we develop a DRL-based algorithm to find the optimal quantization parameters (QPs) by training a deep neural network. The resulting intelligent agent selects the optimal RC strategy to reduce distortion, buffer and quality fluctuations by observing the current state of the encoder. The asynchronous advantage actor-critic (A3C) method is used to solve the MDP problem. Finally, the proposed DRL-based RC method is implemented in the newest video coding standard. Experimental results show that the proposed method offers substantially enhanced RC accuracy and consistently outperforms HEVC reference software and other state-of-the-art algorithms.

Rate Control Method Based on Deep Reinforcement Learning for Dynamic Video Sequences in HEVC

Studies have shown that joint coding is more efficient and effective than independent coding for compression of multiple video programs. Unlike independent coding, joint coding is able to dynamically distribute the channel capacity among video programs according to their respective complexities and hence achieve a more uniform picture quality. This paper examines the bit-allocation issues for joint coding of multiple video programs and provides a bit-allocation strategy that results in a uniform picture quality among programs as well as within a program. To prevent the encoder/decoder buffers from overflowing and underflowing, further constraints on bit allocation are also discussed.

Bit allocation and constraints for joint coding of multiple video programs

This paper presents mathematical frameworks of temporal predictive processing in the MPEG video compression standard. The coding gain is derived based on traditional prediction theories. The optimum ordering of three different picture types (I,P,B-pictures) is clarified according to the image source characteristics. A novel framework of the target bit assignment is presented with some experimental backgrounds. The solution consists of simple formulae, but provides drastic SNR gains to the conventional TM5 algorithm.

Mathematical analysis of MPEG compression capability and its application to rate control

ISO/IEC MPEG-2 Test Model 5 (TM5) describes a rate control method which consists of three steps: bit allocation, rate control and modulation (ISO/MPEG II, Test Model 5, April 1993). There are, however, two problems associated with TM5 rate control: degradation in picture quality at scene cuts and nonuniform picture quality due to buffer-dependent variations of the quantization parameter. This paper presents a new rate control approach which addresses these issues. To eliminate the impact of scene cuts on the picture quality, the first scheduled P picture in a new scene is coded as an I picture, and the extra I picture is further balanced by coding the next scheduled I picture as a P picture. To achieve a relatively uniform picture quality, the same global quantization parameter is applied to all the macroblocks in a picture. The global quantization parameter is determined by using either an iterative or a binary search algorithm. The simulation results demonstrate that a significant improvement in performance is obtained using the proposed rate control approach.

Rate control for MPEG video coding

ISO/IEC MPEG-2 Test Model 5 (TM5) describes a rate control method which consists of three steps: bit allocation, rate control and modulation. There are basically two problems with the TM5 rate control. First, the quantization parameter for a macroblock is fully dependent upon the channel buffer fullness. Hence, macroblocks in a picture may not all be treated equally because of variations in buffer fullness, which may result in nonuniform picture quality. Secondly, the TM5 rate control does not handle scene changes properly because the target bit rate for a picture is determined based only on the information obtained from encoding of the pervious pictures. This paper presents a rate control approach which addressed these two problems associated with the TM5 rate control. A single quantization parameter is used for each picture, which guarantees that all the macroblocks in a picture are treated equally. To address the impact of scene changes on picture quality, we propose to code the first scheduled P picture after scene change as an I picture and the I picture in the following group of picture as a P picture. The simulation results demonstrate that a significant improvement is obtained using the proposed rate control.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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Rate control for MPEG video coding

Rate control for MPEG video coding