By Topic

Generalized PCRTT Offline Bandwidth Smoothing Based on SVM and Systematic Video Segmentation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Zilei Wang ; Lab. of Network Commun. Syst. & Control, Univ. of Sci. & Technol. of China, Hefei, China ; Hongsheng Xi ; Guo Wei ; Qing Chen

As a trade-off technique, bandwidth smoothing can reduce the client buffer requirements and simultaneously keep transmission scheme as smooth as possible. In this paper, bandwidth smoothing is formulated into a binary classification problem of the underflow and overflow points. We propose a novel method to solve that problem based on support vector machine (SVM). Our method is proven to be able to achieve the minimum buffer requirements of constant rate transmission and transport. Furthermore, it directly computes the transmission rate without exhaustively searching buffer size and startup delay. Besides this method, this paper provides a systematic video segmentation algorithm, which can intelligently partition the playback curve into some unequal segments to naturally track the trends of playback curve. The smoothing results with the playback curve of y = x n demonstrate that this video systematic segmentation requires smaller than half of the buffer of the equal segmentation algorithm. Finally, we construct a generalized piecewise constant rate transmission and transport algorithm with SVM and the systematic video segmentation method. The experiments of some real MPEG4 and H.264 video data confirmed the efficiency of our proposed algorithm.

Published in:

IEEE Transactions on Multimedia  (Volume:11 ,  Issue: 5 )