An E cient Content-Based Video Coding Method for Distance Learning Applications

This paper presents a novel method for cooperative educational dissemination systems. Taking into consideration the inherent characteristics of distance learning video streams (existence of a few slow moving objects in a classroom), we have proposed a novel content-based video coding method that is very e cient at low bitrate channels. On the encoding side, we have applied a background subtraction algorithm for motion segmentation using a novel statistical background modeling approach. At each frame, the moving objects are extrapolated with a rectangular model and tracked frame by frame (which forms the only data needed to be sent over the channel). On the decoding side, we have used a new error concealment algorithm (based on edge information of frames) to eliminate probable channel errors in the received data. Moreover, a new fuzzy scene modeling algorithm is proposed that adaptively computes the alpha blending coe cient (used in dynamic video mosaicing) and reconstructs the original video scene from partially overlapped frames. Our experiments show that the proposed coding system is very e cient in real-time video webcasting with approximately 24 fps for CIF formatted sequences (and at a minimum of 13 fps transmission for 720 576 frame sizes). Applying our proposed system has reduced the required bitrate of H.264 and MPEG-4 coding standards by about 2.5% to 8%, respectively, with almost the same, or even better, reconstructed video qualities.