- Gede Sukadarmika Universitas Udayana
- Dewa Made Wiharta Universitas Udayana
- Nyoman Putra Sastra Universitas Udayana
The object trace has been a problem in estimating an object position when the object is moving due to the heavy influence of the uncertainty. Many researcher claim that color histogram is reliable feature to represent this object. . Different investigators use different color spaces in conducting research on tracking the object. So, there is no numerical comparison of the impact of the use of different color spaces to the successful tracking. This study compare the performance of tracking an object by using a different color space i.e.: RGB, HSV, and CIELAB. The performance is shown numerically by comparing the actual position of the object with the results of the estimation.
Candy J. V. (2009). “Bayesian Signal Processing : Classical, Modern, and Particle Filtering Methods”, JohnWiley & Sons, Inc., New Jersey.
Comaniciu, D., Ramesh, V., dan Meer, P. (2003), “Kernel-based object tracking”, IEEE Transactions on Pattern Analysis and Machine Intelligence 25: 564-577.
Doucet, A., de Freitas, N., dan Gordon, N. (2001), “An introduction to sequential Monte Carlo methods”, in Sequential Monte Carlo Methods in Practice, New York: Springer-Verlag.
Doucet, A., Godsill, S., dan Andrieu, C. (2000), “On Sequential Monte Carlo sampling methods for Bayesian filtering”, Statistics and Computing 10(3): 197-208.
Gordon, N.J., Salmond, D.J., dan Smith, A.F.M. (1993), “Novel approach to nonlinear and non-Gaussian state estimation”, Proc.Inst. Elect. Eng.
Kailath, T. (1967), “The divergence and Bhattacharyya distance measures in signal selection”, IEEE Trans.Commun. Tech. 15: 52-60.
Lu, W., Okuma, K., dan Little, J. (2009), “Tracking and recognizing actions of multiple hockey players using the boosted particle filter”, Image and Vision Computing 27: 16.
Nummiaro, K., Koller-Meier, E., dan Van Gool L. (2003), “An adaptive color-based particle filter”, Image Vision and Computing: 99-110.
Wiharta, D.M., Hendrantoro, G., dan Wirawan (2010), “NonlinearNon-Gaussian State Estimation Using Particle Filter”, Proceedings The 1st International Conference on Sustainable Technology Development (ICSTD), Bali.
Yilmaz, A., Javed O., Shah M. (2006), ”Object Tracking: A Survey”, ACM Computing Surveys, Vol. 38, No. 4.
Laptev, I. (2009). Improving object detection with boosted histograms. Image Vis. Comput. 27, 535–544.
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