A Framework for Advanced Video Traces: Evaluating Visual Quality for Video Transmission Over Lossy Networks
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A Framework for Advanced Video Traces: Evaluating Visual Quality for Video Transmission Over Lossy Networks Osama A. Lotfallah,1 Martin Reisslein,2 and Sethuraman Panchanathan1 1 Department 2 Department
of Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, USA of Electrical Engineering, Arizona State University, Tempe, AZ 85287-5706, USA
Received 11 March 2005; Revised 1 August 2005; Accepted 4 October 2005 Conventional video traces (which characterize the video encoding frame sizes in bits and frame quality in PSNR) are limited to evaluating loss-free video transmission. To evaluate robust video transmission schemes for lossy network transport, generally experiments with actual video are required. To circumvent the need for experiments with actual videos, we propose in this paper an advanced video trace framework. The two main components of this framework are (i) advanced video traces which combine the conventional video traces with a parsimonious set of visual content descriptors, and (ii) quality prediction schemes that based on the visual content descriptors provide an accurate prediction of the quality of the reconstructed video after lossy network transport. We conduct extensive evaluations using a perceptual video quality metric as well as the PSNR in which we compare the visual quality predicted based on the advanced video traces with the visual quality determined from experiments with actual video. We find that the advanced video trace methodology accurately predicts the quality of the reconstructed video after frame losses. Copyright © 2006 Osama A. Lotfallah et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1.
INTRODUCTION
The increasing popularity of video streaming over wireless networks and the Internet require the development and evaluation of video transport protocols that are robust to losses during the network transport. In general, the video can be represented in three different forms in these development and evaluation efforts using (1) the actual video bit stream, (2) a video trace, and (3) a mathematical model of the video. The video bit stream allows for transmission experiments from which the visual quality of the video that is reconstructed at the decoder after lossy network transport can be evaluated. On the downside, experiments with actual video require access to and experience in using video codecs. In addition, the copyright limits the exchange of long video test sequences, which are required to achieve statistically sound evaluations, among networking researchers. Video models attempt to capture the video traffic characteristics in a parsimonious mathematical model and are still an ongoing research area; see for instance [1, 2]. Conventional video traces characterize the video encoding, that is, they contain the size (in bits) of each encoded video frame and the corresponding visual quality
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