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Browsing by Author "Tekalp, A. M."

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    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.
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    3-D motion estimation and wireframe adaptation including photometric effects for model-based coding of facial image sequences
    (IEEE, 1994-06) Bozdağı, G.; Tekalp, A. M.; Onural, L.
    We propose a novel formulation where 3-D global and local motion estimation and the adaptation of a generic wireframe model to a particular speaker are considered simultaneously within an optical flow based framework including the photometric effects of the motion. We use a flexible wireframe model whose local structure is characterized by the normal vectors of the patches which are related to the coordinates of the nodes. Geometrical constraints that describe the propagation of the movement of the nodes are introduced, which are then efficiently utilized to reduce the number of independent structure parameters. A stochastic relaxation algorithm has been used to determine optimum global motion estimates and the parameters describing the structure of the wireframe model. Results with both simulated and real facial image sequences are provided.
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    DCT coding of nonrectangularly sampled images
    (IEEE, 1994) Gündüzhan, E.; Çetin, A. Enis; Tekalp, A. M.
    Discrete cosine transform (DCT) coding is widely used for compression of rectangularly sampled images. In this letter, we address efficient DCT coding of nonrectangularly sampled images. To this effect, we discuss an efficient method for the computation of the DCT on nonrectangular sampling grids using the Smith-normal decomposition. Simulation results are provided.
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    An improvement to MBASIC algorithm for 3-D motion and depth estimation
    (IEEE, 1994) Bozdağı, G.; Tekalp, A. M.; Onural, L.
    In model-based coding of facial images, the accuracy of motion and depth parameter estimates strongly affects the coding efficiency. MBASIC is a simple and effective iterative algorithm (recently proposed by Aizawa et al.) for 3-D motion and depth estimation when the initial depth estimates are relatively accurate. In this correspondence, we analyze its performance in the presence of errors in the initial depth estimates and propose a modification to MBASIC algorithm that significantly improves its robustness to random errors with only a small increase in the computational load.
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    Iterative technique for 3-D motion estimation in videophone applications
    (IEEE, 1994-04) Bozdağı, Gözde; Tekalp, A. M.; Onural, Levent
    In object based coding of facial images, the accuracy of motion and depth parameter estimates strongly affects the coding efficiency. We propose an improved algorithm based on stochastic relaxation for 3-D motion and depth estimation that converges to true motion and depth parameters even in the presence of 50% error in the initial depth estimates. The proposed method is compared with an existing algorithm (MBASIC) in case of different number of point correspondences. The simulation results show that the proposed method provides significantly better results than the MBASIC algorithm.
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    Simultaneous 3-D motion estimation and wire-frame model adaptation including photometric effects for knowledge-based video coding
    (IEEE, 1994) Bozdağı, Gözde; Tekalp, A. M.; Onural, Levent
    We address the problem of 3-D motion estimation in the context of knowledge-based coding of facial image sequences. The proposed method handles the global and local motion estimation and the adaptation of a generic wire-frame to a particular speaker simultaneously within an optical flow based framework including the photometric effects of motion. We use a flexible wire-frame model whose local structure is characterized by the normal vectors of the patches which are related to the coordinates of the nodes. Geometrical constraints that describe the propagation of the movement of the nodes are introduced, which are then efficiently utilized to reduce the number of independent structure parameters. A stochastic relaxation algorithm has been used to determine optimum global motion estimates and the parameters describing the structure of the wire-frame model. For the initialization of the motion and structure parameters, a modified feature based algorithm is used. Experimental results with simulated facial image sequences are given.
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    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.

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