Content-Based Video Coding for Distance Learning

This paper presents a novel video encoding method for cooperative educational dissemination systems. Taking into consideration the inherent characteristics of distance learning video streams, existing a few moving objects in the scene and objects having slow motions, we propose a novel content-based video encoding method which is very efficient on low bandwidth channels. In the encoding process, we apply a background subtraction algorithm for motion segmentation with a novel statistical background modeling. In each frame, the moving objects are extrapolated with rectangular bounding boxes which are the only data send over the low bandwidth channel. In the decoding process, we propose a new scene modeling algorithm based on video mosaicing, to reconstruct the original video scene from the partially overlapped frames. Our conducted experiments show that the proposed encoding and decoding algorithms are very efficient in real-time video webcasting with maximum 18 fps for CIF formatted sequences and produce 8 to 12 percent bitrate saving when compared to the H.264 standard.