Abstract
We propose a scalable video conferencing system that streams High-Definition videos (when bandwidth is sufficient) and ultralow-bitrate (<0.25 kbps) cached facial expressions (when the bandwidth is scarce). Our solution consists of optimized approaches to: (i) choose representative facial expressions from training video frames and (ii) match an incoming Webcam frame against the pre-transmitted facial expressions. To the best of our knowledge, such approach has never been studied in the literature. We evaluate the implemented video conferencing system using Webcam videos captured from 9 subjects. Compared to the state-of-the-art scalable codec, our solution: (i) reduces the bitrate by about 130 times when the bandwidth is scarce, (ii) achieves the same coding efficiency when the bandwidth is sufficient, (iii) allows exercising the tradeoff between initialization overhead and coding efficiency, (iv) performs better when the resolution is higher, and (v) runs reasonably fast before extensive code optimization.