Paper Info
Title
GOP-level transmission distortion modeling for mobile streaming video
Abstract
Unequal loss protection is an effective tool in delivering compressed video streaming over packet-switched networks robustly. A critical component in any unequal-loss-protection scheme is a metric for evaluating the importance of different frames in a Group-Of-Pictures (GOP). In the case of video streaming over 3G mobile networks, packet loss usually corresponds to whole-frame loss due to low bandwidth and small picture size, which results in high error rates and thus most of the existing low-complexity transmission-distortion-estimate models may be ineffective. In this paper, we firstly develop a recursive algorithm to compute the GOP-level transmission distortion at pixel-level precision using pre-computed video information. Based on the study on the propagating behavior of the whole-frame-loss transmission distortion, we then propose a piecewise linear-fitting approach to achieve low-complexity transmission distortion modeling. The simulation results demonstrate that the proposed two models are accurate and robust. The proposed transmission distortion models are fast and accurate importance assessment tools in allocating limited channel resources optimally for the mobile streaming video.
Year
DOI
Venue
2008
10.1016/j.image.2007.12.002
Sig. Proc.: Image Comm.
Keywords
Field
DocType
mobile network,unequal loss protection,proposed transmission distortion model,existing low-complexity transmission-distortion-estimate model,gop-level transmission distortion,gop-level transmission distortion modeling,pre-computed video information,packet loss,whole-frame-loss transmission distortion,low-complexity transmission distortion modeling,accurate importance assessment tool,error rate,piecewise linear,recursive algorithm
Data transmission,Group of pictures,Computer science,Packet loss,Real-time computing,Artificial intelligence,Distortion,Computer vision,Transmission loss,Simulation,Communication channel,Bandwidth (signal processing),Data compression
Journal
Volume
Issue
ISSN
23
2
Signal Processing: Image Communication
Citations 
PageRank 
References 
12
0.82
16
Authors
4
Name
Order
Citations
PageRank
Chongyang Zhang18421.63
Hua Yang210721.51
Yu Song335652.74
Xiaokang Yang43581238.09