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Creators/Authors contains: "Shin, M.C."

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  1. ; ; (, IEEE Computer Society Conference on Computer Vision and Pattern Recognition)
    This paper presents a task-oriented evaluation methodology for edge detectors. Performance is measured based on the task of structure from motion. Eighteen real image sequences from 2 different scenes varying in the complexity and scenery types are used. The task-level ground truth for each image sequence is manually specified in terms of the 3D motion and structure. An automated tool computes the accuracy of the motion and structure achieved using the set of edge maps. Parameter sensitivity and execution speed are also analyzed. Four edge detectors are compared. All implementations and data sets are publicly available. 
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  2. ; ; ; (, International Conference on Pattern Recognition)
    We present a method for 3D non-rigid motion tracking and structure reconstruction from 2D points and curve segments from a sequence of perspective images. The 3D locations of features in the first frame are known. The 3D affine motion model is used to describe the nonrigid motion. The results from synthetic and real data are presented. The applications include: lip tracking, MPEG4 face player, and burn scar assessment. The results show that: 1) curve segments are more robust under noise (observed from synthetic data with different Gaussian noise level); and 2) using both feature yields a significant performance gain in real data. 
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  3. ; ; ; (, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics))
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