Publisher : The Korean Institute of Information and Commucation Engineering
DOI : 10.6109/jkiice.2015.19.10.2417
Title & Authors
Improved Mean-Shift Tracking using Adoptive Mixture of Hue and Saturation Park, Han-dong; Oh, Jeong-su;
Mean-Shift tracking using hue has a problem that it fail in the object tracking when background has similar hue to the object. This paper proposes an improved Mean-Shift tracking algorithm using new data instead of a hue. The new data is generated by adaptive mixture of hue and saturation which have low interrelationship . That is, the proposed algorithm selects a main attribute of color that is able to distinguish the object and background well and a secondary one which don't, and places their upper 4 bits on upper 4 bits and lower 4 bits on the mixture data, respectively. The proposed algorithm properly tracks the object, keeping tracking error maximum 2.0~4.2 pixel and average 0.49~1.82 pixel, by selecting the saturation as the main attribute of color under tracking environment that background has similar hue to the object.
A. Yulmaz, O. Javed and M. Shah, "Object tracking: A survey," ACM Computing Surveys (CSUR), vol. 38 no.4 (13), 2006.
S. Weng, C. Kuo and S. Tu “Video object tracking using adaptive Kalman filter,” Journal of Visual Communication and Image Representation vol. 17, no. 6, pp. 1190–1208, 2006.
Y. Mae, Y. Shirai, J. Miura and Y, Kuno, "Object Tracking in Clustered Background Based on Optical Flow and Edges," Pattern Recognition, 1996, Proc. of the 13th International Conf.. vol. 1, 1996.
D. Comaniciu and P. Meer, “Mean Shift: A Robust Approach Toward Feature Space Analysis,” IEEE Transactions on PAMI, vol.24, no.5, 2002.
D. Comaniciu, V. Ramesh, and P. Meer, “Kernel-Based Object Tracking,” IEEE Transactions on PAMI, vol. 25, no. 5, 2003.
N. S. Peng and J. Yang, "Mean-Shift Blob Tracking with Kernel-Color Distribution Estimate and Adaptive Model Update Criterion," Lecture Notes in Computer Science, vol. 3247, pp83-93, 2004.
J. Ning, L. Zhang, D. Zhang, and C. Wu, “Robust Mean Shift Tracking with Corrected Background-Weighted Histogram,” IET Computer Vision, vol. 6, no. 1, pp. 62-69, 2012.
J. H. Lee, W. H. Lee, and D. S. Jeong, "Object tracking method using back-projection of multiple color histogram models," In Circuits and Systems, 2003. ISCAS'03. Proc. of the 2003 International Symposium on, vol. 2, pp. II-668, 2003.
H. Wang and D. Suter, “Color Image Segmentation Using GlobalInformation and Local Homogeneity,” Proc. of 7th Conf. of DICTA, 2003.