[1]段喜萍,刘家锋,王建华,等.多模态特征联合稀疏表示的视频目标跟踪[J].哈尔滨工程大学学报,2015,(12):1609-1613.[doi:10.11990/jheu.201412012]
 DUAN Xiping,LIU Jiafeng,WANG Jianhua,et al.Visual target tracking via multi-cue joint sparse representation[J].hebgcdxxb,2015,(12):1609-1613.[doi:10.11990/jheu.201412012]
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多模态特征联合稀疏表示的视频目标跟踪(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2015年12期
页码:
1609-1613
栏目:
出版日期:
2015-12-25

文章信息/Info

Title:
Visual target tracking via multi-cue joint sparse representation
作者:
段喜萍123 刘家锋1 王建华23 唐降龙1
1. 哈尔滨工业大学 计算机科学与技术学院, 黑龙江 哈尔滨 150001;
2. 哈尔滨师范大学 计算机科学与信息工程学院, 黑龙江 哈尔滨 150025;
3. 黑龙江省智能教育与信息工程重点实验室, 黑龙江 哈尔滨 150025
Author(s):
DUAN Xiping123 LIU Jiafeng1 WANG Jianhua23 TANG Xianglong1
1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;
2. College of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China;
3. Heilongjiang Provincial Key Laboratory of Intelligence Education and Information Engineering, Harbin 150025, China
关键词:
计算机视觉视频目标跟踪多模态LBPAPG模板更新联合稀疏表示
分类号:
TP391
DOI:
10.11990/jheu.201412012
文献标志码:
A
摘要:
针对复杂跟踪环境下,单模态方法不能很好地跟踪目标的问题,提出了一种基于多模态特征联合稀疏表示的目标跟踪方法。该方法对每个候选样本的多模态特征进行联合稀疏表示,将各模态重建误差之和用于计算候选样本的观察概率,并将具有最大观察概率的候选样本确定为目标。通过与其他一些流行跟踪算法进行对比实验,结果表明本方法在遮挡、光照变化等场景下均能可靠跟踪,具有更好的跟踪效果,从而验证了方法的可行性。

参考文献/References:

[1] ROSS D A, LIM J, LIN R S, et al. Incremental learning for robust visual tracking[J]. International Journal of Computer Vision, 2008, 77(1-3): 125-141.
[2] KWON J, LEE K M. Visual tracking decomposition[C]//2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). San Francisco,USA, 2010: 1269-1276.
[3] GRABNER H, GRABNER M, BISCHOF H. Real-time tracking via on-line boosting[C]//Proceedings of BMVC. Edinburgh, 2006: 47-56.
[4] GRABNER H, LEISTNER C, BISCHOF H. Semi-supervised on-line boosting for robust tracking[M]//Computer Vision-ECCV 2008. Berlin: Springer, 2008: 234-247.
[5] BABENKO B, YANG M H, BELONGIE S. Robust object tracking with online multiple instance learning[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(8): 1619-1632.
[6] ZHANG K, ZHANG L, YANG M H. Real-time compressive tracking[C]//European Conference on Computer Vision. Florence, Italy, 2012: 864-877.
[7] MEI Xue, LING Haibin. Robust visual tracking and vehicle classification via sparse representation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(11): 2259-2272.
[8] MEI Xue, LING Haibin, WU Yi, et al. Minimum error bounded efficient e1 tracker with occlusion detection[C]//2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Colorado Springs,USA, 2011: 1257-1264.
[9] LI H, SHEN C, SHI Q. Real-time visual tracking using compressive sensing[C]//2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Colorado Springs, USA, 2011: 1305-1312.
[10] WU Yi, BLASCH E, CHEN Genshe, et al. Multiple source data fusion via sparse representation for robust visual tracking[C]//2011 Proceedings of the 14th International Conference on Information Fusion (FUSION). Chicago,USA, 2011: 1-8.
[11] DUAN Xiping, LIU Jiafeng, TANG Xianglong. Multi-cue visual tracking based on sparse representation[M]//Intelligence Science and Big Data Engineering. Berlin: Springer, 2013: 427-434.
[12] WANG Yuru, TANG Xianglong, CUI Qing. Dynamic appearance model for particle filter based visual tracking[J]. Pattern Recognition, 2012, 45(12): 4510-4523.
[13] YUAN Xiaotong, LIU Xiaobai, YAN Shuicheng. Visual classification with multitask joint sparse representation[J]. IEEE Transactions on Image Processing, 2012, 21(10): 4349-4360.

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备注/Memo

备注/Memo:
收稿日期:2014-12-04;改回日期:。
基金项目:国家自然科学基金资助项目(61173087);黑龙江省教育厅科学基金资助项目(12541238).
作者简介:段喜萍(1980-),女,讲师,博士研究生;唐降龙(1960-),男,教授,博士生导师.
通讯作者:段喜萍,E-mail:xpduan_1999@126.com.
更新日期/Last Update: 2016-01-07