RATE-DISTORTION OPTIMIZED VIDEO FRAME DROPPING ON ACTIVE NETWORK NODES

We propose a rate-distortion optimized video frame dropping strategy that can be applied on active network nodes in case of heavy traffic load. Our approach relies on side information that is sent along with the video bit-streams. The side information consists of a rate vector containing the frame size (in bytes) of every picture as well as a distortion matrix describing the reconstruction distortion (in MSE) observed for a Group of Pictures given a certain frame loss pattern. In contrast to QoS-based approaches, our scheme offers larger flexibility and supports dynamic frame importance control. When comparing our rate-distortion optimized dropping concept with priority-based dropping strategies, significantly improved reconstruction quality is observed. Improvements of up to 8dB are obtained for our simulation setup.

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