Robust infrared target tracking using thermal information in Mean-Shift

被引:1
作者
Yun, Sungmin [1 ]
Kim, Sungho [1 ]
机构
[1] Yeungnam Univ, Dept Elect Engn, 280 Daehak Ro, Gyongsan 38541, Gyeongsangbuk D, South Korea
来源
PATTERN RECOGNITION AND TRACKING XXX | 2019年 / 10995卷
基金
新加坡国家研究基金会;
关键词
Infrared; Temperature; Image contrast; Mean-Shift; Object tracking; Pedestrian tracking; OBJECT TRACKING; FILTERS;
D O I
10.1117/12.2519191
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The basic computational module of the technique is an old pattern recognition procedure: the mean-shift. In case of gray level feature domain, the spatial information of the target is lost when the background brightness histogram is the same as the target histogram. In this paper, we propose a new algorithm that is independent of background contrast by changing features from a conventional brightness based histogram to a temperature-based histogram. The proposed algorithm can track targets robustly regardless to target-background contrast. The experiment results demonstrate that the temperature-based Mean-Shift outperforms comparing with the brightness-based Mean-Shift when track a object with successive background variations.
引用
收藏
页数:6
相关论文
共 20 条
[1]  
[Anonymous], 2017, P IEEE C COMP VIS PA
[2]  
[Anonymous], 2017, CVPR
[3]  
[Anonymous], 2016, CVPR
[4]  
[Anonymous], 2017, 31 AAAI C ART INT
[5]  
Comaniciu D, 2000, PROC CVPR IEEE, P142, DOI 10.1109/CVPR.2000.854761
[6]   Deep tracking in the wild: End-to-end tracking using recurrent neural networks [J].
Dequaire, Julie ;
Ondruska, Peter ;
Rao, Dushyant ;
Wang, Dominic ;
Posner, Ingmar .
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2018, 37 (4-5) :492-512
[7]   Re3: Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects [J].
Gordon, Daniel ;
Farhadi, Ali ;
Fox, Dieter .
IEEE ROBOTICS AND AUTOMATION LETTERS, 2018, 3 (02) :788-795
[8]   Robust object tracking based on local region sparse appearance model [J].
Han, Guang ;
Wang, Xingyue ;
Liu, Jixin ;
Sun, Ning ;
Wang, Cailing .
NEUROCOMPUTING, 2016, 184 :145-167
[9]   Robust Object Tracking via Key Patch Sparse Representation [J].
He, Zhenyu ;
Yi, Shuangyan ;
Cheung, Yiu-Ming ;
You, Xinge ;
Tang, Yuan Yan .
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 47 (02) :354-364
[10]   Learning to Track at 100 FPS with Deep Regression Networks [J].
Held, David ;
Thrun, Sebastian ;
Savarese, Silvio .
COMPUTER VISION - ECCV 2016, PT I, 2016, 9905 :749-765