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http://dx.doi.org/10.6109/jkiice.2015.19.6.1477

A Fast Moving Object Tracking Method by the Combination of Covariance Matrix and Kalman Filter Algorithm  

Lee, Geum-boon (Department of Computer Security, Chosun College of Science & Technology)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.19, no.6, 2015 , pp. 1477-1484 More about this Journal
Abstract
This paper proposes a robust method for object tracking based on Kalman filters algorithm and covariance matrix. As a feature of the object to be tracked, covariance matrix ensures the continuity of the moving target tracking in the image frames because the covariance is addressed spatial and statistical properties as well as the correlation properties of the features, despite the changes of the form and shape of the target. However, if object moves faster than operation time, real time tracking is difficult. In order to solve the problem, Kalman filters are used to estimate the area of the moving object and covariance matrices as a feature vector are compared with candidate regions within the estimated Kalman window. The results show that the tracking rate of 96.3% achieved using the proposed method.
Keywords
Fast Moving Object Tracking; Covariance Matrix; Kalman Filter; Averaging Search Rate;
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