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http://dx.doi.org/10.9717/kmms.2012.15.3.336

Improvement Method of Tracking Speed for Color Object using Kalman Filter and SURF  

Lee, Hee-Jae (가톨릭대학교 디지털미디어학과 미디어공학전공)
Lee, Sang-Goog (가톨릭대학교 디지털미디어학부)
Publication Information
Journal of Korea Multimedia Society / v.15, no.3, 2012 , pp. 336-344 More about this Journal
Abstract
As an important part of the Computer Vision, the object recognition and tracking function has infinite possibilities range from motion recognition to aerospace applications. One of methods to improve accuracy of the object recognition, are uses colors which have robustness of orientation, scale and occlusion. Computational cost for extracting features can be reduced by using color. Also, for fast object recognition, predicting the location of the object recognition in a smaller area is more effective than lowering accuracy of the algorithm. In this paper, we propose a method that uses SURF descriptors which applied with color model for improving recognition accuracy and combines with Kalman filter which is Motion estimation algorithm for fast object tracking. As a result, the proposed method classified objects which have same patterns with different colors and showed fast tracking results by performing recognition in ROI which estimates future motion of an object.
Keywords
Real time object recognition; Color descriptor; SURF; Kalman filter;
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Times Cited By KSCI : 2  (Citation Analysis)
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