2D Planar Object Tracking using Improved Chamfer Matching Likelihood 


Vol. 17,  No. 1, pp. 37-46, Feb.  2010
10.3745/KIPSTB.2010.17.1.37


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  Abstract

In this paper we have presented a two dimensional model based tracking system using improved chamfer matching. Conventional chamfer matching could not calculate similarity well between the object and image when there is very cluttered background. Then we have improved chamfer matching to calculate similarity well even in very cluttered background with edge and corner feature points. Improved chamfer matching is used as likelihood function of particle filter which tracks the geometric object. Geometric model which uses edge and corner feature points, is a discriminant descriptor in color changes. Particle Filter is more non-linear tracking system than Kalman Filter. Then the presented method uses geometric model, particle filter and improved chamfer matching for tracking object in complex environment. In experimental result, the robustness of our system is proved by comparing other methods.

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[IEEE Style]

C. M. Oh, M. H. Jeong, B. J. You, C. W. Lee, "2D Planar Object Tracking using Improved Chamfer Matching Likelihood," The KIPS Transactions:PartB , vol. 17, no. 1, pp. 37-46, 2010. DOI: 10.3745/KIPSTB.2010.17.1.37.

[ACM Style]

Chi Min Oh, Mun Ho Jeong, Bum Jae You, and Chil Woo Lee. 2010. 2D Planar Object Tracking using Improved Chamfer Matching Likelihood. The KIPS Transactions:PartB , 17, 1, (2010), 37-46. DOI: 10.3745/KIPSTB.2010.17.1.37.

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