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About: Kanade–Lucas–Tomasi feature tracker     Goto   Sponge   NotDistinct   Permalink

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Type: programming language New Facet based on Instances of this Class

In computer vision, the Kanade–Lucas–Tomasi (KLT) feature tracker is an approach to feature extraction. It is proposed mainly for the purpose of dealing with the problem that traditional image registration techniques are generally costly. KLT makes use of spatial intensity information to direct the search for the position that yields the best match. It is faster than traditional techniques for examining far fewer potential matches between the images.