Multiplexing video traffic using frame-skipping aggregation technique.

by Alan Yeung.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.Includes bibliographical references (leaves 53-[56]).Abstract also in Chinese.Chapter 1 --- Introduction --- p.1Chapter 2 --- MPEG Overview --- p.5Chapter 3 --- Framework of Frame-Skipping Lossy Aggregation --- p.10Chapter 3.1 --- Video Frames Delivery using Round-Robin Scheduling --- p.10Chapter 3.2 --- Underflow Safety Margin on Receiver Buffers --- p.12Chapter 3.3 --- Algorithm in Frame-Skipping Aggregation Controller --- p.13Chapter 4 --- Replacement of Skipped Frames in MPEG Sequence --- p.17Chapter 5 --- Subjective Assessment Test on Frame-Skipped Video --- p.21Chapter 5.1 --- Test Settings and Material --- p.22Chapter 5.2 --- Choice of Test Methods --- p.23Chapter 5.3 --- Test Procedures --- p.25Chapter 5.4 --- Test Results --- p.26Chapter 6 --- Performance Study --- p.29Chapter 6.1 --- Experiment 1: Number of Supportable Streams --- p.31Chapter 6.2 --- Experiment 2: Frame-Skipping Rate When Multiplexing on a Leased T3 Link --- p.33Chapter 6.3 --- Experiment 3: Bandwidth Usage --- p.35Chapter 6.4 --- Experiment 4: Optimal USMT --- p.38Chapter 7 --- Implementation Considerations --- p.41Chapter 8 --- Conclusions --- p.45Chapter A --- The Construction of Stuffed Artificial B Frame --- p.48Bibliography --- p.5

An optimal bandwidth allocation strategy for the delivery of compressed prerecorded video

The transportation of prerecorded, compressed video data without loss of picture quality requires the network and video servers to support large fluctuations in bandwidth requirements. Fully utilizing a client-side buffer for smoothing bandwidth requirements can limit the fluctuations in bandwidth required from the underlying network and the video-on-demand servers. This paper shows that, for a fixed-size buffer constraint, the critical bandwidth allocation technique results in plans for continuous playback of stored video that have (1) the minimum number of bandwidth increases, (2) the smallest peak bandwidth requirements, and (3) the largest minimum bandwidth requirements. In addition, this paper introduces an optimal bandwidth allocation algorithm which, in addition to the three critical bandwidth allocation properties, minimizes the total number of bandwidth changes necessary for continuous playback. A comparison between the optimal bandwidth allocation algorithm and other critical bandwidth-based algorithms using 17 full-length movie videos and 3 seminar videos is also presented.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42314/1/530-5-5-297_70050297.pd

Improving motion estimation with evolvable search algorithms

Until now the topic of motion estimation, as used in video compression, has been dominated by search methodologies which are modifications of an exhaustive search. This research takes a completely new approach by applying two evolvable search algorithms, the Genetic Algorithm and the Genetic Program, to the area of motion estimation. The main purpose of this research is to determine the applicability of evolvable search methods to the topic of motion estimation. Several methods are studied: in the first application, a Genetic Algorithm is used to determine individual motion vectors one at a time, while the second method explores the use of a Genetic Algorithm to search for all of the motion vectors to correlate two frames simultaneously. To reduce the number of motion vectors required, Genetic Programming is applied to variable block size motion estimation. Finally, this work is expanded by applying it to region motion estimation, which is not restricted to using square or rectangular motion blocks

Video compression with complete information for pre-recorded sources

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 123-130).by David Michael Baylon.Ph.D

An Algorithm for Lossless Smoothing of MPEG Video

Interframe compression techniques, such as those used in MPEG video, give rise to a coded bit stream where picture sizes differ by a factor of 10 or more. As a result, buffering is needed to reduce (smooth) rate fluctuations of encoder output from one picture to the next; without smoothing, the performance of networks that carry such video traffic would be adversely affected. Various techniques have been suggested for controlling the output rate of a VBR encoder to alleviate network congestion or prevent buffer overflow. Most of these techniques, however, are lossy, and should be used only as a last resort. In this paper, we design and specify an algorithm for lossless smoothing. The algorithm is characterized by three parameters: D (delay bound), K (number of pictures with known sizes), and H (lookahead interval for optimization). We present a theorem which guarantees that, if K 1, the algorithm finds a solution that satisfies the delay bound. (Although the algorithm and theorem we..

Abstract An Algorithm for Lossless Smoothing of MPEG Video*

Interframe compression techniques, such as those used in MPEG video, give rise to a coded bit stream where picture sizes differ by a factor of 10 or more. As a result, bufTering is needed to reduce (smooth) rate fluctuations of encoder output from one picture to the next; without smoothing, the performance of networks that carry such video traffic would be adversely affected. Various techniques have been suggested for controlling the output rate of a VBR encoder to alleviate network congestion or prevent btier overflow. Most of these techniques, however} are 10SSU,and should be used only as a last resort. In this paper, we design and specify an algorithm for fossless smoothing. The algorithm is characterized by three parameters: D (delay bound), K (number of pictures with known sizes), and H (lookahead interval). We present a theorem which guarantees that, if K ~ 1, the algorithm finds a solution that satisfies the delay bound. (Although the algorithm and theorem were moti-vated by MPEG video, they are applicable to the smooth-ing of compressed video in general.) To study performance characteristics of the algorithm, we conducted a large num-ber of experiments using statistics from four MPEG video sequences.