Abstract
A method is developed to track planar and near-planar objects by incorporating a model of the expected image template distortion, and fitting the sampling region to pre-trained examples with general regression. The approach does not assume a particular form of the underlying space, allows a natural handling of occluding objects, and permits dynamic changes of the scale and size of the sampled region. The implementation of the algorithm runs comfortably in modest hardware at video-rate.
Translated title of the contribution | Tracking with General Regression |
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Original language | English |
Article number | 65-72 |
Pages (from-to) | 65 - 72 |
Number of pages | 8 |
Journal | Machine Vision and Applications |
Volume | 19 (1) |
DOIs | |
Publication status | Published - Jan 2008 |