Browse > Article
http://dx.doi.org/10.6109/jkiice.2015.19.3.636

Object Tracking Using CAM shift with 8-way Search Window  

Kim, Nam-Gon (Department of Computer Engineering, Chosun University)
Lee, Geum-Boon (Department of Computer Security, Chosun College of Science & Technology)
Cho, Beom-Joon (Department of Computer Engineering, Chosun University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.19, no.3, 2015 , pp. 636-644 More about this Journal
Abstract
This research aims to suggest methods to improve object tracking performance by combining CAM shift algorithm with 8-way search window, and reduce arithmetic operation by reducing the number of frame used for tracking. CAM shift has its adverse effect in tracking methods using signature color or having difficulty in tracking rapidly moving object. To resolve this, moving search window of CAM shift makes it possible to more accurately track high-speed moving object after finding object by conducting 8-way search by using information at a final successful timing point from a timing point missing tracking object. Moreover, hardware development led to increased unnecessary arithmetic operation by increasing the number of frame produced per second, which indicates efficiency can be enhanced by reducing the number of frame used in tracking to reduce unnecessary arithmetic operation.
Keywords
Tracking; Search; CAM shift; Search Window;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 P. Vadakkepat, P. Lim, L. C. De silva, L. jing, L. L. Ling, "Multimodal Apporach to Human-face Detection and Tracking", IEEE Trans. on Industrial Electronics, Vol. 55, No. 3, 2008.
2 D Comaniciu and P Meer, "Mean shift: A robust Approach Toward Feature Space Analysis," IEEE Transactions on Pattern Analysis and machine Intellegence, Vol. 24, No. 5, pp. 603-619, 2002.   DOI
3 D. Exner, E. Bruns, D. Kurz, A. Grundhofer, O. Bimber, "Fast and robust CAMshift tracking", IEEE Computer Society Conf. on Computer Vision and Pattern Recognition Workshops, pp. 9-16, 2010.
4 G. R. Bradski, "Computer vision face tracking for use in a perceptual user interface," Intel Technology Journal, 2nd Quarter, 1998.
5 Y.G. Kim, "A Study on Genetic Programming based Generation of the Color Model and Moving Object Tracking using Improved CAMSHIFT Algorithm", SEO KYEONG univ, M.S. dissertation, 2011.
6 Fang Xu, Jun Cheng, and Chao Wang,"Real time face tracking using particle filtering and mean shift," IEEE International Conference on Automation and Logics, pp. 2252-2255, 2008.
7 Frat R. Bradski, "Computer Vision Face Tracking For Use in a Perceptual User Interface," Intel Technologt journal, Vol. 2, No. 2, pp. 12-21 1998.
8 D. Y. Kim, J. W. Park, C. W. Lee "Object-Tracking System Using Combination of CAMshift and Kalman filter Algorithm," Journal of Korea Multimedia Society Vol. 16, No. 5, 2013. 5, pp. 619-628.   DOI   ScienceOn
9 J. S. Shin, D. S. Kang "A Study on Moving Object Tracking Algorithm Using Depth Information and SURF Algorithm," 2012 Korean Institute Of Information Technology pp. 144-148 2012. 5.
10 C. Yang, R Duraiswami, and L. Davis "Fast Multiple Object Tracking via a Hierarchical Particle Filter," International Conference on Computer Vision, Vol. 1, pp. 212-219, 2005. 11.
11 K. Deguchi, O. Kawanaka, and T. Okatani,"Object tracking by the mean-shift of regional color distribution combined with the particle-filter algorithm," 17th International Conference on Parttern Recognition, Vol. 3, pp. 506-509, 2004.