Visual Vehicle Tracking Based on Deep Representation and Semisupervised Learning
Joint Authors
Wang, Hai
Cai, Yingfeng
Sun, Xiaoqiang
Chen, Long
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-09
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Discriminative tracking methods use binary classification to discriminate between the foreground and background and have achieved some useful results.
However, the use of labeled training samples is insufficient for them to achieve accurate tracking.
Hence, discriminative classifiers must use their own classification results to update themselves, which may lead to feedback-induced tracking drift.
To overcome these problems, we propose a semisupervised tracking algorithm that uses deep representation and transfer learning.
Firstly, a 2D multilayer deep belief network is trained with a large amount of unlabeled samples.
The nonlinear mapping point at the top of this network is subtracted as the feature dictionary.
Then, this feature dictionary is utilized to transfer train and update a deep tracker.
The positive samples for training are the tracked vehicles, and the negative samples are the background images.
Finally, a particle filter is used to estimate vehicle position.
We demonstrate experimentally that our proposed vehicle tracking algorithm can effectively restrain drift while also maintaining the adaption of vehicle appearance.
Compared with similar algorithms, our method achieves a better tracking success rate and fewer average central-pixel errors.
American Psychological Association (APA)
Cai, Yingfeng& Wang, Hai& Sun, Xiaoqiang& Chen, Long. 2017. Visual Vehicle Tracking Based on Deep Representation and Semisupervised Learning. Journal of Sensors،Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1187201
Modern Language Association (MLA)
Cai, Yingfeng…[et al.]. Visual Vehicle Tracking Based on Deep Representation and Semisupervised Learning. Journal of Sensors No. 2017 (2017), pp.1-6.
https://search.emarefa.net/detail/BIM-1187201
American Medical Association (AMA)
Cai, Yingfeng& Wang, Hai& Sun, Xiaoqiang& Chen, Long. Visual Vehicle Tracking Based on Deep Representation and Semisupervised Learning. Journal of Sensors. 2017. Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1187201
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1187201