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A new approach to object tracking using local linear embedding method

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2 Author(s)
Jing Gao ; Eng. Coll., Signal & Inf. Process. Lab., Air Force Eng. Univ., Xi''an, China ; Duyan Bi

This paper presents a new approach to using locally linear embedding (LLE) method in object tracking problems. By means of measuring the divergence of the K nearest neighbors of test data, a novel method is proposed to distinguish object from background directly through the LLE embedding results. Avoiding training a mapping function, this approach is less dependent on a beforehand training set of object compare to other attempts of utilizing manifold embedding method on object tracking. Besides, an asymmetric version of LLE is derived to improve the tracking performance. A Bayesian inference framework is built to apply this approach to visual tracking problem using particle filter. Experimental results demonstrate both efficiency and adaptability of our algorithm.

Published in:

Image and Signal Processing (CISP), 2010 3rd International Congress on  (Volume:1 )

Date of Conference:

16-18 Oct. 2010