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Dynamic feature point tracking in an image sequence
Yi-Sheng Yao; Chellappa, R.;
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
Volume 1,
9-13 Oct. 1994
Page(s):654
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657 vol.1
Abstract:
This paper presents a model-based algorithm for tracking feature points over a long sequence of monocular noisy images with the ability to include new feature points detected in successive frames. The trajectory for each feature point is modeled by a simple kinematic motion model. A probabilistic data association filter is first designed to estimate the motion between two consecutive frames. A matching algorithm then identifies the corresponding point to sub-pixel accuracy and an extended Kalman filter (EKF) is employed to continuously track the feature point. An efficient way to dynamically include new feature points from successive frames into a tracking list is also addressed. Tracking results for two image sequences are given
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