Rate-Distortion Optimized Frame Dropping for Multiuser Streaming and Conversational Videos

Abstract

We consider rate-distortion optimized strategies for dropping frames from multiple conversational and streaming videos sharing limited network node resources. The dropping strategies are based on side information that is extracted during encoding and is sent along the regular bitstream. The additional transmission overhead and the computational complexity of the proposed frame dropping schemes are analyzed. Our experimental results show that a significant improvement in end-to-end performance is achieved compared to priority-based random early dropping.