Browsing by Author "Toklu, C."

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Open Access
2-D triangular mesh-based mosaicking for object tracking in the presence of occlusion
(SPIE, 1997) Toklu, C.; Tekalp, A. M.; Erdem, A. Tanju
In this paper, we describe a method for temporal tracking of video objects in video clips. We employ a 2D triangular mesh to represent each video object, which allows us to describe the motion of the object by the displacements of the node points of the mesh, and to describe any intensity variations by the contrast and brightness parameters estimated for each node point. Using the temporal history of the node point locations, we continue tracking the nodes of the 2D mesh even when they become invisible because of self-occlusion or occlusion by another object. Uncovered parts of the object in the subsequent frames of the sequence are detected by means of an active contour which contains a novel shape preserving energy term. The proposed shape preserving energy term is found to be successful in tracking the boundary of an object in video sequences with complex backgrounds. By adding new nodes or updating the 2D triangular mesh we incrementally append the uncovered parts of the object detected during the tracking process to the one of the objects to generate a static mosaic of the object. Also, by texture mapping the covered pixels into the current frame of the video clip we can generate a dynamic mosaic of the object. The proposed mosaicing technique is more general than those reported in the literature because it allows for local motion and out-of-plane rotations of the object that results in self-occlusions. Experimental results demonstrate the successful tracking of the objects with deformable boundaries in the presence of occlusion.
Open Access
Tracking motion and intensity variations using hierarchical 2-D mesh modeling for synthetic object transfiguration
(1996-11) Toklu, C.; Erdem, A. T.; Sezan, M. I.; Tekalp, A. M.
We propose a method for tracking the motion and intensity variations of a 2-D mildly deformable image object using a hierarchical 2-D mesh model. The proposed method is applied to synthetic object transfiguration, namely, replacing an object in a real video clip with another synthetic or natural object via digital postprocessing. Successful transfiguration requires accurate tracking of both motion and intensity (contrast and brightness) variations of the object-to-be-replaced so that the replacement object can be rendered in exactly the same way from a single still picture. The proposed method is capable of tracking image regions corresponding to scene objects with nonplanar and/or mildly deforming surfaces, accounting for intensity variations, and is shown to be effective with real image sequences.