In:
Advanced Materials Research, Trans Tech Publications, Ltd., Vol. 989-994 ( 2014-7), p. 3605-3608
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.
Type of Medium:
Online Resource
ISSN:
1662-8985
DOI:
10.4028/www.scientific.net/AMR.989-994
DOI:
10.4028/www.scientific.net/AMR.989-994.3605
Language:
Unknown
Publisher:
Trans Tech Publications, Ltd.
Publication Date:
2014
detail.hit.zdb_id:
2265002-7
