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Interactive Feature Tracking using K-D Trees and Dynamic Programming
2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06)
A new approach to template tracking is presented, incorporating three distinct contributions. Firstly, an explicit definition for a feature track is given. Secondly, the advantages of an image preprocessing stage are demonstrated and, in particular, the effectiveness of highly compressed image patch data stored in k-d trees for fast and discriminatory image patch searches. Thirdly, the k-d trees are used to generate multiple track hypotheses which are efficiently merged to give the optimal
doi:10.1109/cvpr.2006.158
dblp:conf/cvpr/BuchananF06
fatcat:dat3vri7unck7jwaxxncj4mhua