N-tier Simultaneous Modelling and Tracking for Arbitrary Warps
Dowson, NDH and Bowden, R (2006) N-tier Simultaneous Modelling and Tracking for Arbitrary Warps In: BMVC 2006, 2006-09-04 - 2006-09-07, Edinburgh, UK.
Available under License : See the attached licence file.
This paper presents an approach to object tracking which, given a single example of a target, learns a hierarchical constellation model of appearance and structure on the fly. The model becomes more robust over time as evidence of the variability of the object is acquired and added to the model. Tracking is performed in an optimised Lucas-Kanade type framework, using Mutual Information as a similarity metric. Several novelties are presented: an improved template update strategy using Bayes theorem, a multi-tier model topology, and a semi-automatic testing method. A critical comparison with other methods is made using exhaustive testing. In all 11 challenging test sequences were used with a mean length of 568 frames.
|Item Type:||Conference or Workshop Item (Conference Poster)|
|Divisions :||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Identification Number :||10.5244/C.20.59|
|Additional Information :||© The authors. Published by The British Machine Vision Association (BMVA).|
|Depositing User :||Symplectic Elements|
|Date Deposited :||21 May 2012 14:06|
|Last Modified :||23 Sep 2013 19:24|
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