JOURNAL ARTICLE

Retrieving quality video across heterogeneous networks. Video over wireless

José M. F. MouraRadu JasinschiHirohisa ShiojiriJyh-Cherng Lin

Year: 1996 Journal:   IEEE Personal Communications Vol: 3 (1)Pages: 44-54   Publisher: Institute of Electrical and Electronics Engineers

Abstract

The article addresses the issues that arise in delivering video across Wireless Andrew. Wireless Andrew is the Carnegie Mellon University (CMU) heterogeneous networking environment. It interconnects wideband and narrowband wireless and wired networks using off-the-shelf technologies. The authors design a video system where video servers distributed across the network deliver, upon request, video clips to clients scattered around the campus. The main novelty of the article is generative video (GV), a content-based meta representation for video that is well suited for the heterogeneous dynamic environment of Wireless Andrew. GV provides a framework for graceful degradation as end-to-end network throughput varies. GV reduces the video sequence to a small set of still images and side information needed to reconstruct the original sequence. The authors have demonstrated for three real live video sequences that GV delivers compression ratios in the range of 1000-10000 with good perceptual quality They develop a scalable implementation for the GV coder/decoder (codec). Scalability coding avoids duplicating the encoding of each video clip when servicing a wide range of throughputs, as in heterogeneous networks. They discuss the video delivery requirements, the video system architecture, the system implementation, and the trade-offs needed to ensure graceful degradation under real-life network operating conditions.

Keywords:
Computer science Codec Video tracking Computer network Wireless network Video quality Scalability Video processing Real-time computing Scalable Video Coding Wireless Uncompressed video Quality of service Telecommunications Computer hardware

Metrics

22
Cited By
5.74
FWCI (Field Weighted Citation Impact)
14
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Analysis and Summarization
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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