Adaptive image feature reduction for object tracking
Lin, Cong; Pun, Chi-Man
Conference Name4th International Conference on Materials Science and Information Technology, MSIT 2014
Source PublicationAdvanced Materials Research
Conference Date6 14, 2014 - 6 15, 2014
Conference PlaceTianjin, China
Author of SourceTrans Tech Publications Ltd
AbstractA 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. © (2014) Trans Tech Publications, Switzerland.
Fulltext Access
Citation statistics
Document TypeConference paper
CollectionUniversity of Macau
AffiliationUniversity of Macau, Macau SAR, China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Lin, Cong,Pun, Chi-Man. Adaptive image feature reduction for object tracking[C]//Trans Tech Publications Ltd,2014:3605-3608.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Lin, Cong]'s Articles
[Pun, Chi-Man]'s Articles
Baidu academic
Similar articles in Baidu academic
[Lin, Cong]'s Articles
[Pun, Chi-Man]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Lin, Cong]'s Articles
[Pun, Chi-Man]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.