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.
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Research supported by Grants GR/N03266 and GR/S97774 from the UK Engineering and Physical Science Research Council, and by a Mexican CONACYT scholarship to WWM.
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Mayol, W.W., Murray, D.W. Tracking with general regression. Machine Vision and Applications 19, 65–72 (2008). https://doi.org/10.1007/s00138-007-0087-x
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DOI: https://doi.org/10.1007/s00138-007-0087-x