Mon, 07 Jul 2008 16:41:41 BST CiteULike: p2pstreaming analysis http://www.citeulike.org/user/p2pstreaming/tag/analysis CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/p2pstreaming/article/2822354 <i>Circuits and Systems for Video Technology, IEEE Transactions on, Vol. 10, No. 1. (2000), pp. 63-67.</i><br /><br />We propose an analytically tractable approach to model compressed video traffic called C-DAR(1). The C-DAR(1) model combines an approach utilizing a discrete-time Markov chain with a continuous-time Markov chain. We show that this approach accurately models the distribution and exponential autocorrelation characteristics of video conferencing traffic. Also, we show that by comparing our analytical results against a simulation using actual video conferencing data, our model provides realistic results. In addition to presenting this new approach, we address the effects of long-range dependencies (LRD) in the video traffic. Based on our analytical and simulation results, we are able to conclude that the LRD have minimal impact on videoconference traffic modeling An analytically tractable model for video conference traffic Shugong Xu Zailu Huang Yan Yao doi:10.1109/76.825860 Circuits and Systems for Video Technology, IEEE Transactions on, Vol. 10, No. 1. (2000), pp. 63-67. 2008-05-22T06:02:15-00:00 2000 Circuits and Systems for Video Technology, IEEE Transactions on 10 1 63 67 analysis conferencing video http://www.citeulike.org/user/p2pstreaming/article/499800 <i>ACM Trans. Multimedia Comput. Commun. Appl., Vol. 1, No. 4. (November 2005), pp. 354-376.</i> An analytical study of peer-to-peer media streaming systems Yi-Cheng Tu Jianzhong Sun Mohamed Hefeeda Sunil Prabhakar doi:10.1145/1111604.1111607 ACM Trans. Multimedia Comput. Commun. Appl., Vol. 1, No. 4. (November 2005), pp. 354-376. 2006-02-09T04:10:18-00:00 2005 ACM Trans. Multimedia Comput. Commun. Appl. 1551-6857 1 4 354 376 ACM Press analysis peer streaming to http://www.citeulike.org/user/p2pstreaming/article/599036 <i>Signal Processing Magazine, IEEE, Vol. 17, No. 6. (2000), pp. 12-36.</i><br /><br />Multimedia content analysis refers to the computerized understanding of the semantic meanings of a multimedia document, such as a video sequence with an accompanying audio track. With a multimedia document, its semantics are embedded in multiple forms that are usually complimentary of each other, Therefore, it is necessary to analyze all types of data: image frames, sound tracks, texts that can be extracted from image frames, and spoken words that can be deciphered from the audio track. This usually involves segmenting the document into semantically meaningful units, classifying each unit into a predefined scene type, and indexing and summarizing the document for efficient retrieval and browsing. We review advances in using audio and visual information jointly for accomplishing the above tasks. We describe audio and visual features that can effectively characterize scene content, present selected algorithms for segmentation and classification, and review some testbed systems for video archiving and retrieval. We also describe audio and visual descriptors and description schemes that are being considered by the MPEG-7 standard for multimedia content description Multimedia content analysis-using both audio and visual clues Yao Wang Zhu Liu Jin-Cheng Huang Signal Processing Magazine, IEEE, Vol. 17, No. 6. (2000), pp. 12-36. 2006-04-25T00:57:57-00:00 2000 Signal Processing Magazine, IEEE 17 6 12 36 analysis content multimedia