Abstract
Detecting motion of objects in images, while the camera is moving, is a complicated task. In this paper, we propose a novel method to effectively solve this problem by using Neural Network and Kalman Filter. This technique uses parameters of camera motion to overcome problems caused by error in the image processing outputs. We have implemented this technique in the MRL Middle Size Soccer Robots. The experimental results show a low error rate of 2.2% which suggests that the combined approach performs significantly better than the traditional techniques.
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Taleghani, S., Aslani, S., Shiry, S. (2009). Robust Moving Object Detection from a Moving Video Camera Using Neural Network and Kalman Filter. In: Iocchi, L., Matsubara, H., Weitzenfeld, A., Zhou, C. (eds) RoboCup 2008: Robot Soccer World Cup XII. RoboCup 2008. Lecture Notes in Computer Science(), vol 5399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02921-9_55
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DOI: https://doi.org/10.1007/978-3-642-02921-9_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02920-2
Online ISBN: 978-3-642-02921-9
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