Abstract
The application of the traditional Camshift algorithm, which exhibits a good tracking performance in case of the obvious color characters, meanwhile, is limited in the target tracking in the color space. A fast tracking algorithm based on gray value distribution and distance kernel space is proposed. A 1.5D gray histogram method is designed to describe the model of moving object, which improves the reduction of computation for the back projection and real-time tracking performance. Moreover, a distance kernel function, describing the object weights, is constructed so as to handle the background disturbance and occlusion problem. Experiment results demonstrate the efficiency of proposed algorithm, that it can achieve a fast object tracking and resist background disturbance in some level.
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Acknowledgments
This work is partly supported by theNatural Science Foundation (Grant No.60903005).
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© 2013 Springer-Verlag Berlin Heidelberg
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Li, W., Xiao, Y., Pan, F., Zhou, K. (2013). A Real-Time Tracking Algorithm Based on Gray Distribution and Distance Kernel Space. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_23
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DOI: https://doi.org/10.1007/978-3-642-38466-0_23
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