A Multistage target tracker in IR image sequences

被引:7
作者
Huang, Qiao [1 ]
Yang, Jie [1 ]
机构
[1] Shanghai Jiao Tong Univ, Inst Image Proc & Pattern Recognit, Key Lab Syst Control & Informat Proc, Minist Educ China, Shanghai 200240, Peoples R China
基金
美国国家科学基金会;
关键词
Target tracking; IR image; SIFT feature; Multistage tracker; OBJECT TRACKING;
D O I
10.1016/j.infrared.2014.03.005
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
In this paper, we propose a robust approach for tracking target in forward looking infrared imagery taken from an airborne moving platform. The tracker is proposed in a two stage algorithm with a coarse to fine manner. First, we introduce a coarse but quick algorithm to roughly locate the target, which based on a model matching procedure by computing the SIFT vector of the target. The raw position and the size of the target are then used to initialize the multistage tracking algorithm. Second, the target's position is refined through a dedicated localization algorithm, which based on a HOG feature tracking procedure to overcome the rapid size and angel changes of the dim target in the IR image sequence. Finally, the target's model can automatically been updated and utilized in the first stage. As confirmed by experimental results on a variety of IR image sequences, the proposed approach efficiently and robustly tracks target under challenging environmental conditions. Moreover, the speed of the multistage algorithm is also convincing in the tested IR imagery. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:122 / 128
页数:7
相关论文
共 21 条
[1]  
[Anonymous], 2005, PROC CVPR IEEE
[2]  
[Anonymous], 2007, Computer Vision and Pattern Recognition
[3]  
Bibby C, 2008, LECT NOTES COMPUT SC, V5303, P831, DOI 10.1007/978-3-540-88688-4_61
[4]   Kernel-based object tracking [J].
Comaniciu, D ;
Ramesh, V ;
Meer, P .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2003, 25 (05) :564-577
[5]  
Comaniciu D, 2000, PROC CVPR IEEE, P142, DOI 10.1109/CVPR.2000.854761
[6]   RANDOM SAMPLE CONSENSUS - A PARADIGM FOR MODEL-FITTING WITH APPLICATIONS TO IMAGE-ANALYSIS AND AUTOMATED CARTOGRAPHY [J].
FISCHLER, MA ;
BOLLES, RC .
COMMUNICATIONS OF THE ACM, 1981, 24 (06) :381-395
[7]   CONDENSATION - Conditional density propagation for visual tracking [J].
Isard, M ;
Blake, A .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 1998, 29 (01) :5-28
[8]  
Jain PK, 2007, THIRD INTERNATIONAL SYMPOSIUM ON 3D DATA PROCESSING, VISUALIZATION, AND TRANSMISSION, PROCEEDINGS, P877
[9]   Infrared target tracking in multiple feature pseudo-color image with kernel density estimation [J].
Liu, Ruiming ;
Lu, Yanhong .
INFRARED PHYSICS & TECHNOLOGY, 2012, 55 (06) :505-512
[10]  
Lowe D. G., 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision, P1150, DOI 10.1109/ICCV.1999.790410