Weighted Sparse Representation Regularized Graph Learning for RGB-T Object Tracking-Reference-Cited by-同舟云学术

Weighted Sparse Representation Regularized Graph Learning for RGB-T Object Tracking

Published:2017-10-23 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 25th ACM international conference on Multimedia
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Author:

Li Chenglong¹,Zhao Nan¹,Lu Yijuan²,Zhu Chengli¹,Tang Jin¹

Affiliation:

1. Anhui University, Hefei, China

2. Texas State University, San Marcos, TX, USA

Funder

Co-Innovation Center for Information Supply & Assurance Technology Anhui University

Texas State Research Enhancement Program

Natural Science Foundation of Anhui Higher Education Institution of China

Key Scientific and Technological Project of State Grid Anhui Electric Power Company

National Science Foundation of United States

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3123266.3123289

Reference50 articles.

1. Thermal–visible registration of human silhouettes: A similarity measure performance evaluation

2. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers

3. F. Bunyak K. Palaniappan S. K. Nath and G. Seetharaman. 2007. Geodesic active contour based fusion of visible and infrared video for persistent object tracking Proceedings of IEEE Workshop on Applications of Computer Vision. 10.1109/WACV.2007.26 F. Bunyak K. Palaniappan S. K. Nath and G. Seetharaman. 2007. Geodesic active contour based fusion of visible and infrared video for persistent object tracking Proceedings of IEEE Workshop on Applications of Computer Vision. 10.1109/WACV.2007.26

4. D. Comaniciu V. Ramesh and P. Meer. 2003. Kernel-based object tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence (2003). 10.1109/TPAMI.2003.1195991 D. Comaniciu V. Ramesh and P. Meer. 2003. Kernel-based object tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence (2003). 10.1109/TPAMI.2003.1195991

5. Thermo-visual feature fusion for object tracking using multiple spatiogram trackers

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