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Using Optical Flow as Evidence for Probabilistic Tracking.

, , , and . SCIA, volume 2749 of Lecture Notes in Computer Science, page 1044-1049. Springer, (2003)

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Local Motion Estimation from Stereo Image Sequences., , , and . IbPRIA, volume 2652 of Lecture Notes in Computer Science, page 740-747. Springer, (2003)Probabilistic Observation Models for Tracking Based on Optical Flow., , , , and . IbPRIA, volume 2652 of Lecture Notes in Computer Science, page 462-469. Springer, (2003)Optical flow-based probabilistic tracking., , , , and . ISSPA (2), page 219-222. IEEE, (2003)0-7803-7946-2.Applying deformable templates for cell image segmentation., and . Pattern Recognit., 33 (5): 821-832 (2000)An optical flow probabilistic observation model for tracking., , , and . ICIP (3), page 957-960. IEEE, (2003)Boundary simplification using a multiscale dominant-point detection algorithm., , and . Pattern Recognit., 31 (6): 791-804 (1998)A New Methodology to Automatically Segment Biomedical Images., , and . ICIAP (2), volume 1311 of Lecture Notes in Computer Science, page 372-379. Springer, (1997)Using Optical Flow as Evidence for Probabilistic Tracking., , , and . SCIA, volume 2749 of Lecture Notes in Computer Science, page 1044-1049. Springer, (2003)Physically-based active shape models: initialization and optimization., and . Pattern Recognit., 31 (8): 1003-1017 (1998)Recovering Non-rigid 3D Shape Using a Plane+Parallax Approach., and . AMDO, volume 2492 of Lecture Notes in Computer Science, page 251-256. Springer, (2002)