2D mesh-based detection and representation of an occluding object for object-based video

In this study, an algorithm for mesh-based detection of occlusion caused by a newly entering object into the scene, which covers the information present in the current frame, and mesh-based representation of it is proposed. A 2D Delaunay triangulated dynamic mesh is initially designed on the first frame of the sequence. The motion of each node is then compared to its average motion. Frames with nodes of high activity, with different directions and forming a region are selected to be analyzed for detection of newly entering object(s) into the scene. A region formed by detection of bad motion vectors is enlarged using a distance criterion. The detected frame and the preceding one are range filtered, The luminance components of these two frames are formed. The difference of the range filtered frames and of their respective luminance components are taken into account. The differences are checked with respect to a threshold value inside the formed region. Pixels exceeding this threshold form the newly entering object. Since there may be separate regions formed by these pixels, mesh-based merging of these regions is then accomplished. The detected newly entering object is then meshed and tracked as a new object in the scene in accordance with the occluded object. The proposed 2D mesh-based occlusion detection and representation method can be applied in object-based video coding, storage and manipulation.