Adaptive Image Feature Reduction for Object Tracking

Cong Lin; Chi Man Pun

doi:10.4028/www.scientific.net/AMR.989-994.3605

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 989-994Adaptive Image Feature Reduction for Object...

Adaptive Image Feature Reduction for Object Tracking

Abstract:

A novel adaptive image feature reduction approach for object tracking using vectorized texture feature is proposed in this paper. Our contributions are three-fold: 1) a statistical discriminative appearance model using texture feature was proposed. 2) Majority of dimensions of the features are removed by judging their errors of the chosen distribution model. The remaining dimensions are most discriminative ones for classification task. The dimension reduction has advantages of reducing the computational cost in classification stage. 3) An adaptive learning rate was proposed to handle drifts caused by long term occlusion. Preliminary experimental results are satisfactory and compared to state-of-the-art object tracking methods.

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Periodical:

Advanced Materials Research (Volumes 989-994)

Pages:

3605-3608

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.989-994.3605

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Online since:

July 2014

Authors:

Cong Lin*, Chi Man Pun

Keywords:

Adaptive Learning Rate, Feature Refining, Object Tracking, Texture Feature

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