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Augmented particle filtering for efficient visual tracking

10 years 28 days ago
Augmented particle filtering for efficient visual tracking
Visual tracking is one of the key tasks in computer vision. The particle filter algorithm has been extensively used to tackle this problem due to its flexibility. However the conventional particle filter uses system transition as the proposal distribution, frequently resulting in poor priors for the filtering step. The main reason is that it is difficult, if not impossible, to accurately model the target's motion. Such a proposal distribution does not take into account the current observations. It is not a trivial task to devise a satisfactory proposal distribution for the particle filter. In this paper we advance a general augmented particle filtering framework for designing the optimal proposal distribution. The essential idea is to augment a second filter's estimate into the proposal distribution design. We then show that several existing improved particle filters can be rationalised within this general framework. Based on this framework we further propose variant algorit...
Chunhua Shen, Michael J. Brooks, Anton van den Hen
Added 23 Oct 2009
Updated 14 Nov 2009
Type Conference
Year 2005
Where ICIP
Authors Chunhua Shen, Michael J. Brooks, Anton van den Hengel
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