| Classical video coding standards such as H.26x and MPEG-1/2 are frame-based techniques, and no segmentation of video scenarios is required. Their high compression performance makes them widely used in video applications. With the proliferation of multimedia information, people are no more satisfied with simple navigation of video contents, but require object-based functionalities. Therefore, MPEG-4 introduces the concept of video object to support content-based functionalities. MPEG-7 defines a universal and normalized description of various multimedia objects. According to the MPEG-4 verification model, video sequence must be segmented into semantic video objects. Their motion, shape and texture information are coded respectively. The main values are: improved coding efficiency by allocating different bit rate to different video object in accordance with their importance to human visual system; object-based scalability so as to obtain better visual effect at low bit rate applications; content-based storage, interactivity and retrieval organizing video content according to video object.Decomposing a video sequence into VOFs is very difficult in this field. An intrinsic problem of VOP generation is that objects of interest are not homogeneous with respect to low-level features such as color, intensity, or optical flow. Thus, conventional segmentation algorithms will fail to obtain meaningful partitions.This paper proposes an algorithm based on Color Interest Point and grads operator, which is different from conventional video object extraction algorithm. Results show that the computation complexity of the algorithm is low, it can track object precisely and it does not make too much more segmentations on an object which is semantic affinity. |
