Good features to track
Jianbo Shi; Tomasi, C.
Computer Vision and Pattern Recognition, 1994. Proceedings CVPR apos;94., 1994 IEEE Computer Society Conference on
Volume , Issue , 21-23 Jun 1994 Page(s):593 - 600
Digital Object Identifier   10.1109/CVPR.1994.323794
Summary:No feature-based vision system can work unless good features can be identified and tracked from frame to frame. Although tracking itself is by and large a solved problem, selecting features that can be tracked well and correspond to physical points in the world is still hard. We propose a feature selection criterion that is optimal by construction because it is based on how the tracker works, and a feature monitoring method that can detect occlusions, disocclusions, and features that do not correspond to points in the world. These methods are based on a new tracking algorithm that extends previous Newton-Raphson style search methods to work under affine image transformations. We test performance with several simulations and experiments

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