- Volume 19 Issue 10
DOI QR Code
Improved Mean-Shift Tracking using Adoptive Mixture of Hue and Saturation
색상과 채도의 적응적 조합을 이용한 개선된 Mean-Shift 추적
- Received : 2015.07.23
- Accepted : 2015.08.28
- Published : 2015.10.31
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.
- 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.
- 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. https://doi.org/10.1016/j.jvcir.2006.03.004
- H. Wang and D. Suter, “Color Image Segmentation Using GlobalInformation and Local Homogeneity,” Proc. of 7th Conf. of DICTA, 2003.
- 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. https://doi.org/10.1109/34.1000236
- D. Comaniciu, V. Ramesh, and P. Meer, “Kernel-Based Object Tracking,” IEEE Transactions on PAMI, vol. 25, no. 5, 2003. https://doi.org/10.1109/TPAMI.2003.1195991
- 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. https://doi.org/10.1049/iet-cvi.2009.0075