多技术融合的Mean-Shift目标跟踪算法

doi:10.6040/j.issn.1672-3961.2.2014.069

Abstract

Abstract: Based on the study of classic algorithm, a Mean-Shift target tracking algorithm fused multi-technology was proposed, and the defects of the classic Mean-Shift tracking algorithm were solved. The center position of target was estimated by the Kalman algorithm. The space information of the target area was extracted using the block color histogram. The combination approach of the background weighted and nuclear weighted was used to suppress the interference of background pixels on the target. The experiments resulted on several video data showed that the new method fused three kinds of technology effectively overcame the barrier and background pixel sensitive problem, and had more accurate tracking than classic Mean-Shift target tracking algorithm under complex environment.

Key words: Mean-Shift algorithm, background weighted, target tracking, block color histogram, Kalman predictor

CLC Number:

TP391.4

GUO Zhibo, DONG Jian, PANG Cheng. A Mean-Shift target tracking algorithm fused multi technology[J].JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2015, 45(2): 10-16.

References

[1] FUKUNAGA K, HOSTETER L D. The estimation of the gradient of a density function with applications in pattern recognition[J]. IEEE Trans Information Theory, 1975, 21:32-40.
[2] CHENG Yizong. Mean-shift, mode seeking, and clustering[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1995, 17(8):790-799.
[3] COMANICIU D, RANMESH V, MEER P. Kemel based object tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(5):564-577.
[4] COMANICIU D, RANMESH V, MEER P. Mean-shift:a robust approach towards festure space analysis[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2002, 24(5):603-619.
[5] 陈少华, 闫钧华. 基于Kalman预测和自适应模板的目标相关跟踪研究[J]. 电子设计工程, 2011, 19(23):189-192. CHEN Shaohua, YAN Junhua. Correlation-based target tracking algorithm based on Kalman prediction and adaptive template[J]. Electronic Design Engineering, 2011, 19(23):189-192.
[6] 党晓军, 尹俊文. 一种基于模板匹配的运动目标跟踪方法[J]. 计算机应用, 2010, 46(5):173-176. DANG Xiaojun, YIN Junwen. Template matching based moving object tracking method[J]. Computer Engineer and Applications, 2010, 46(5):173-176.
[7] ROBERT Collins. Mean-shift blob tracking through scale space[C]//Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. New Jersey, USA: IEEE Press, 2003:234-240.
[8] 彭宁嵩, 杨杰,刘志,等. Mean-shift跟踪算法中核函数窗口宽的自动选取[J].软件学报, 2005, 16(9):1542-1550. PENG Ningsong, YANG Jie, LIU Zhi, et al. Automatic selection of kernel-band width for mean-shift object tracking[J]. Journal of Software, 2005, 16(9):1542-1550.
[9] 贾静平, 柴艳妹. 一种健壮的目标多自由度Mean-Shift序列图像跟踪算法[J]. 中国图像图形学报, 2006, 11(5):707-713. JIA Jingping, CHAI Yanmei. Robust tracking of objects in image sequences using multiple degrees of freedom mean-shift algorithm[J]. Journal of Chinese Image and Graphical, 2006, 11(5):707-713.
[10] 胡铟, 杨静宇. 基于分块颜色直方图的Mean-Shift跟踪算法[J]. 系统仿真学报, 2009,21(10):2936-2939. HU Yin, YANG Jingyu. Tracking algorithm based on block color histogram and mean-shift[J]. Journal of System Simulation, 2009, 21(10):2936-2939.
[11] 张玲,蒋大永. 基于Mean-Shift的改进目标跟踪算法[J]. 计算机应用, 2008, 28(12):3120-3123. ZHANG Ling, JIANG Dayong. Improved target tracking algorithm based on mean-shift[J]. Journal of Computer Application, 2008, 28(12):3120-3123.
[12] BEYAN C, TEMIZEL A. Adaptive mean-shift for automated multi object tracking[J]. Computer Vision, IET, 2013, 6(1):1-12.
[13] CHEN Xiaohui, ZHANG Mengjiao, RUAN Kai, et al. Improved mean-shift target tracking based on self-organizing maps[J]. Signal, Image and Video Processing, 2014, 8(1):103-112.
[14] DENG Yu, LIU Fang, SU Guangda. Mean-shift tracker with chaotic artificial bee colony and space variant resolution[J]. International Journal for Light and Electron Optics, 2014, 125(16):4572-4577.
[15] LANG Fengkai, YANG Jie, LI Deren, et al. Mean-Shift based speckle filtering of polarimetric SAR data[J]. Geoscience and Remote Sensing, 2014, 52(7):4440-4454.
[16] PHADKE G, VELMURUGAN R. Improved mean-shift for multi-target tracking[C]//Procedding of 2013 IEEE International Workshop on Performance Evaluation of Tracking and Surveillance. New Jersey, USA:IEEE Press, 2013:37-44.
[17] SHOU Jen, CHANG Chien, YANG Minshen, et al. On mean-shift-based clustering for circular data[J]. Soft Computing, 2012, 16(6):1043-1060.
[18] TOMAS Vojir, JANA Noskova, JIRI Matas. Robust scale-adaptive mean-shift for tracking[J]. Image Analysis, Lecture Notes in Computer Science, 2013, 7944:652-663.
[19] SIDRAM M H, BHAJANTRI N U. Enhancement of mean-shift tracking through joint histogram of color and color coherence vector[C]//Proceedings of the Second International Conference on Soft Computing for Problem Solving.[S.l.]:Springer India, 2014:547-555.
[20] HATI K K, VARDHANAN A V. Review and improvement areas of Mean-Shift tracking algorithm[C]//Procedding of the 18th IEEE International Symposium on Consumer Electronics. New Jersey, USA: IEEE Press, 2014:22-25.
[21] KALMAN R E. A new approach to linear filtering and prediction problems[J]. Journal of Basix Engineering, 1960, 82(1):35-45.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

A Mean-Shift target tracking algorithm fused multi technology

PDF (PC)

Abstract

Cite this article

share this article

References

Related Articles 5

Metrics

Comments

Recommended 0

[1]	MA Shuaiyifan, ZHAO Zijian. Surgical navigation system based on anartificialmarker [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(3): 63-68.
[2]	GE Kairong, CHANG Faliang, DONG Wenhui. Sparse representation tracking method based on locality sensitive histogram [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2014, 44(5): 14-19.
[3]	QIU Xiaoxin1,2, ZHANG Wenqiang1,2*, QIN Jinxian1,2, DU Zhengyang1,2, ZHANG Defeng1,2. Multi-target real-time tracking method under harsh environment [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2014, 44(2): 21-27.
[4]	Yue Khing Toh¹， XIAO Wendong²， XIE Lihua¹. Wireless sensor network for distributed target tracking: practices via real test bed development [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 50-56.
[5]	MA Li,CHANG Faliang,QIAO Yizheng . Nonrigid target tracking based on genetic algorithm and particle filter [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(3): 26-29 .