Robust 2D Feature Tracking in Long Video Sequences


The KIPS Transactions:PartB , Vol. 14, No. 7, pp. 473-480, Dec. 2007
10.3745/KIPSTB.2007.14.7.473,   PDF Download:

Abstract

Feature tracking in video frame sequences has suffered from the instability and the frequent failure of feature matching between two successive frames. In this paper, we propose a robust 2D feature tracking method that is stable to long video sequences. To improve the stability of feature tracking, we predict the spatial movement in the current image frame using the state variables. The predicted current movement is used for the initialization of the search window. By computing the feature similarities in the search window, we refine the current feature positions. Then, the current feature states are updated. This tracking process is repeated for each input frame. To reduce false matches, the outlier rejection stage is also introduced. Experimental results from real video sequences showed that the proposed method performs stable feature tracking for long frame sequences.


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Cite this article
[IEEE Style]
J. H. Yoon and J. S. Park, "Robust 2D Feature Tracking in Long Video Sequences," The KIPS Transactions:PartB , vol. 14, no. 7, pp. 473-480, 2007. DOI: 10.3745/KIPSTB.2007.14.7.473.

[ACM Style]
Jong Hyun Yoon and Jong Seung Park. 2007. Robust 2D Feature Tracking in Long Video Sequences. The KIPS Transactions:PartB , 14, 7, (2007), 473-480. DOI: 10.3745/KIPSTB.2007.14.7.473.