Journal of Guangxi Normal University(Natural Science Edition) ›› 2017, Vol. 35 ›› Issue (3): 37-44.doi: 10.16088/j.issn.1001-6600.2017.03.005

Previous Articles     Next Articles

Tracking Infrared-visible Target with Joint Histogram

CAI Bing, ZHANG Canlong*, LI Zhixin   

  1. Guangxi Key Lab of Multi-source Information Mining and Security, Guilin Guangxi 541004, China
  • Online:2017-07-25 Published:2018-07-25

PDF (PC)

169

Abstract: Due to traditional kernel tracking algorithm can only track infrared or visible target, its performance is poor, even unsuccessful. This paper proposes a fusion tracking method for infrared-visible target by using a mean shift algorithm. Firstly, the histogram is still adopted to represent the infrared target and visible target, and the similarity between infrared candidate and its target, and the similarity between visible candidate and its target, are integrated into a novel objective function with different weight. Secondly, similar to mean shift on the objective function, a joint target location-shift formula is induced to the new method. Finally, the optimal target location is gained recursively by applying the mean shift procedure. Experimental results of several infrared-visible image sequences demonstrate that the proposed fusion algorithm is superior to the single-sensor tracking algorithm in handling illumination change and background clutter.

Key words: mean shift, histogram, fusion tracking, infrared-visible, similarity

CLC Number: 

  • TP391.41
[1] COMANICIU D, RAMESH V, MEER P. Kernel-based object tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2003,25(5):564-577.DOI:10.1109/TPAMI.2003.1195991.
[2] WU Yi, LIM J, YANG M H. Online object tracking: a benchmark[C]//IEEE Conference on Computer Vision and Pattern Recognition. Los Alamitos, CA: IEEE Computer Society,2013:2411-2418.DOI:10.1109/CVPR.2013.312.
[3] ZHANG Weizheng, JI Jiangao, JING Zhongzhao, et al. Adaptive real-time compressive tracking[C]// International Conference on Network and Information Systems for Computers. Piscataway, NJ:IEEE Press, 2015:236-240. DOI:10.1109/ICNISC.2015.152.
[4] 齐苑辰,吴成东,陈东岳,等. 基于稀疏表达的超像素跟踪算法[J].电子与信息学报,2015,37(3):529-535. DOI:10.11999/JEIT140374.
[5] LEICHTER I. Mean Shift Trackers with cross-bin metrics[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(4):695-706.DOI:10.1109/TPAMI.2011.167.
[6] 张灿龙,唐艳平,李志欣,等. 基于二阶空间直方图的双核跟踪[J].电子与信息学报,2015,37(7):1660-1666. DOI:10.11999/JEIT141321.
[7] ZHANG Shunli, SUI Yao, YU Xin, et al. Hybrid support vector machines for robust object tracking[J]. Pattern Recognition,2015,48(8):2474-2488.DOI:10.1016/j.patcog.2015.02.008.
[8] ZHANG Kaihua, SONG Huihui. Real-time visual tracking via online weighted multiple instance learning[J]. Pattern Recognition,2013,46(1):397-411.DOI:10.1016/j.patcog.2012.07.013.
[9] 刘哲,陈恳,郑紫微. 基于HOG与多实例在线学习的目标跟踪算法[J].计算机工程,2015,41(1):158-163. DOI:10.3969/j.issn.1000-3428.2015.01.029.
[10] ROSS D A, LIM J, LIN R S, et al. Incremental learning for robust visual tracking[J]. International Journal of Computer Vision,2008,77(1/2/3):125-141.DOI:10.1007/s11263-007-0075-7.
[11] MEI Xue, LING Haibin. Robust visual tracking using 1 minimization[C]//IEEE 12th International Conference on Computer Vision. Piscataway, NJ:IEEE Press, 2009:1436-1443.DOI:10.1109/ICCV.2009.5459292.
[12] LIU Huaping, SUN Fuchun. Fusion tracking in color and infrared images using joint sparse representation[J]. Science China Information Sciences,2012,55(3):590-599.DOI:10.1007/s11432-011-4536-9.
[13] 赵高鹏,薄煜明,陈益. 多特征提取的红外和可见光目标跟踪方法[J].兵工学报,2011,32(4):445-451.
[14] YUN Xiao, JING Zhongliang, XIAO Gang, et al. A compressive tracking based on time-space Kalman fusion model[J]. Science China Information Sciences,2016,59(1):1-15.DOI:10.1007/s11432-015-5356-0.
[15] LIU Yanjun, TONG Shaocheng, CHEN C L P. Adaptive fuzzy control via observer design for uncertain nonlinear systems with unmodeled dynamics[J]. IEEE Transactions on Fuzzy Systems,2013,21(2):275-288.DOI: 10.1109/TFUZZ.2012.2212200.
[16] XIAO Gang, YUN Xiao, WU Jianmin. A multi-cue mean-shift target tracking approach based on fuzzified region dynamic image fusion[J]. Science China Information Sciences,2012,55(3):577-589. DOI:10.1007/s11432-012-4553-3.
[1] NIE Yu, LIAO Xiangwen, WEI Jingjing, YANG Dingda, CHEN Guolong. Multi-label Classification Based on the Deep Autoencoder [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(1): 71-79.
[2] ZHANG Canlong, SU Jiancai, LI Zhixin, WANG Zhiwen. Infrared-Visible Target Tracking Basedon AdaBoost Confidence Map [J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(4): 42-50.
[3] LI Ziyan,LIU Weiming. New Method of Moving Vehicle Detection Based on Partial HOG Feature [J]. Journal of Guangxi Normal University(Natural Science Edition), 2017, 35(3): 1-13.
[4] TANG Qiling, CHEN Zhilin, ZHOU Shanyi. Geographic Division of Chinese Ants (Hymenoptera: Formicidae) Based on Generic Category [J]. Journal of Guangxi Normal University(Natural Science Edition), 2017, 35(1): 82-91.
[5] XIA Haiying. Cervical Cell Images Segmentation Based on Improved SLIC Region Merging [J]. Journal of Guangxi Normal University(Natural Science Edition), 2016, 34(4): 93-100.
[6] SUN Shui-fa, LI Le-peng, DONG Fang-min, ZOU Yao-bin, CHEN Peng. Bi-histogram Equalization Based on Partially Overlapped Sub-block with Iterative Threshold [J]. Journal of Guangxi Normal University(Natural Science Edition), 2013, 31(3): 119-126.
[7] WANG Feng, JIN Xiao-bo, YU Jun-wei, WANG Gui-cai. V-optimal Histogram and Its Application in License Plate Classification [J]. Journal of Guangxi Normal University(Natural Science Edition), 2013, 31(3): 138-143.
[8] MA Ying-cang, ZHANG Mei, CUI Mei-ying. Truth Degree Theory of 3-valued Fuzzy Logic System Based onFrank Triangular Norm [J]. Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(3): 84-88.
[9] MENG Fan-hui, WANG Hao, FANG Bao-fu, PENG Wei. Research and Implementation of Human Detection Based on ExtendedHistograms of Oriented Gradients [J]. Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(3): 168-172.
[10] SHA Bei-bei, XIE Li-cong. Algorithm to Cluster Search Results Based on Frequent Itemsets [J]. Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(2): 151-155.
[11] ZHOU Xin, HAO Zhi-feng, CAI Rui-chu, WEN Wen. Text Clustering with Noise and It's Application in Anti-spam Systems [J]. Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(2): 156-160.
[12] ZHANG Xin-ming, ZHANG Yu-shan, LI Zhen-yun. Image Thresholding Method Based on Improved Moment Preserving [J]. Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(2): 185-190.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Guangxi Normal University(Natural Science Edition), All Rights Reserved.
Tel: 0773-5857325　E-mail: gxsdzkb@mailbox.gxnu.edu.cn
Powered by Beijing Magtech Co. Ltd