Evaluating the streaming of FGS-encoded video with rate-distortion traces

The MPEG-4 video coding standard has recently been enriched with Fine Granularity Scalability (FGS) a new coding technique expressly designed for video streaming. With FGS coding the video stream can be flexibly truncated at very fine granularity to adapt to the available network resources. In this report we provide a framework for the evaluation of the streaming of FGS-encoded video. The framework consists of evaluation metrics and a library of rate-distortion traces. This framework enables networking researchers without access to video codecs and video sequences to develop and evaluate rate-distortion optimized streaming mechanisms for FGS-encoded video. We apply our evaluation framework to investigate the rate-distortion optimized streaming at different video frame aggregation levels. We find that compared to the optimization for each individual video frame, optimization at the level of video scenes reduces the computational effort dramatically, while reducing the video quality only very slightly.