Real-time content-based processing of multicast video

The access of high bandwidth multimedia data is generally limited to the network due to the limited network resources, inefficient indexing mechanism and less of semantic interpretations. Currently, most content-based video content representation involves the segmentation and indexing of video based on scene change and camera/object motion, and such research generally performs off-line video processing. Little research has been done on on-line video processing, which is crucial in video communication applications such as video conferencing, video multicasting and on-line video browsing and retrieval. This research investigates real-time content-based processing of multicast video over the Internet. New on-line video feature extraction schemes, such as scene change detection, on-line key frame classification, are considered to meet the requirement of real-time video multicasting filtering based on the user's profile over the Internet. The annotation and features extracted from a multicast videoconference bitstream by the on-line video content analysis proxies, which are using the proposed video processing algorithms, are output to a separate metadata channel for the further assistance of semantic multicasting of video content. The performance of the proposed algorithms is also demonstrated.