Video coding using motion classification

In this paper we present a video coding approach similar to texture- based methods but based on motion models. We consider motion perception properties instead of spatial texture properties of the video sequence. We integrate a motion classification algorithm to separate foreground objects containing noticeable motion from the background. These background areas are labeled as skipped areas that are not encoded. After decoding, frame reconstruction is performed by inserting the skipped background into the decoded frames. We are able to show as much as 15% an improvement over previous texture- based implementations in terms of video compression efficiency.