Good features to track

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Good features to track (1994)

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by Jianbo Shi , Carlo Tomasi

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2050 - 14 self

BibTeX

@MISC{Shi94goodfeatures,
    author = {Jianbo Shi and Carlo Tomasi},
    title = {Good features to track},
    year = {1994}
}

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Abstract

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.

Keyphrases

good feature physical point feature monitoring method feature-based vision system feature selection criterion solved problem previous newton-raphson style search method affine image transformation several simulation

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