Machine Vision and Applications

, Volume 19, Issue 1, pp 65–72 | Cite as

Tracking with general regression

Original Paper

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.

Keywords

Real-time tracking Non-parametric regression Kernel methods 

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of BristolBristolUK
  2. 2.Department of Engineering ScienceUniversity of OxfordOxfordUK

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