A Study on Effective Moving Object Segmentation and Fast Tracking Algorithm


The KIPS Transactions:PartB , Vol. 9, No. 3, pp. 359-368, Jun. 2002
10.3745/KIPSTB.2002.9.3.359,   PDF Download:

Abstract

In this paper, we propose effective boundary line extraction algorithm for moving objects by matching error image and moving vectors, and fast tracking algorithm for moving object by partial boundary lines. We extracted boundary line for moving object by generating seeds with probability distribution function based on Watershed algorithm, and by extracting boundary line for moving objects through extending seeds, and then by using moving vectors. We processed tracking algorithm for moving object by using a part of boundary lines as features. We set up a part of every-direction boundary line for moving object as the initial feature vectors for moving objects. Then, we tracked moving object within current frames by using feature vector for the previous frames. As the result of the simulation for tracking moving object on the real images, we found that tracking processing of the proposed algorithm was simple due to tracking boundary line only for moving object as a feature, in contrast to the traditional tracking algorithm for active contour line that have varying processing cost with the length of boundary line. The operations was reduced about 39% as contrasted with the full search BMA. Tracking error was less than 4 pixel when the feature vector was [15x5] through the information of every-direction boundary line. The proposed algorithm just needed 200 times of search operation.


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Cite this article
[IEEE Style]
Y. S. Cho and J. S. Lee, "A Study on Effective Moving Object Segmentation and Fast Tracking Algorithm," The KIPS Transactions:PartB , vol. 9, no. 3, pp. 359-368, 2002. DOI: 10.3745/KIPSTB.2002.9.3.359.

[ACM Style]
Young Seok Cho and Ju Shin Lee. 2002. A Study on Effective Moving Object Segmentation and Fast Tracking Algorithm. The KIPS Transactions:PartB , 9, 3, (2002), 359-368. DOI: 10.3745/KIPSTB.2002.9.3.359.