Abstract
A novel evolutionary algorithm called Probability Evolutionary Algorithm (PEA), and a method based on PEA for visual tracking of human body are presented. PEA is inspired by the Quantum computation and the Quantum-inspired Evolutionary Algorithm, and it has a good balance between exploration and exploitation with very fast computation speed. In the PEA based human tracking framework, tracking is considered to be a function optimization problem, so the aim is to optimize the matching function between the model and the image observation. Then PEA is used to optimize the matching function. Experiments on synthetic and real image sequences of human motion demonstrate the effectiveness, significance and computation efficiency of the proposed human tracking method.
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References
Hu, W.M., Tan, T.N., Wang, L., Maybank, S.J.: A survey on visual surveillance of object motion and behaviors. IEEE Trans. on System Man and Cybernetics 34, 334–351 (2004)
Gavrila, D., Davis, L.: 3D model based tracking of humans inaction: A multiview approach. In: IEEE Proceedings of International Conference on Computer Vision and Pattern Recognition, San Francisco, California, pp. 73–80 (1996)
Isard, M., Blake, A.: CONDENSATION-conditional density propagation for visual tracking. International Journal of Computer Vision 29, 5–28 (1998)
Deutscher, J., Davidson, A., Reid, I.: Articulated partitioning of high dimensional search spaces associated with articulated body motion capture. In: IEEE Proceedings of International Conference on Computer Vision and Pattern Recognition, Hawaii, pp. 669–676 (2001)
Wu, Y., Hua, G., Yu, T.: Tracking Articulated Body by Dynamic Markov Network. In: Proceedings of the Ninth IEEE International Conference on Computer Vision, pp. 1096–1101 (2003)
Zhao, T., Nevatia, R.: Tracking Multiple Humans in Crowded Environment. In: IEEE Proceedings of International Conference on Computer Vision and Pattern Recognition, pp. 342–349 (2004)
Han, K.H., Kim, J.H.: Quantum-Inspired Evolutionary Algorithm for a Class of Combinatorial Optimization. IEEE Trans. on Evolutionary Computing 6, 580–593 (2002)
Hey, T.: Quantum computing: An introduction. Computing & Control Engineering Journal 10, 105–121 (1996)
Shen, S.H., Jiang, W.K., Chen, W.R.: Research of Probability Evolutionary Algorithm. In: 8th International Conference for Young Computer Scientists, Beijing, pp. 93–97 (2005)
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Shen, S., Chen, W. (2006). Probability Evolutionary Algorithm Based Human Body Tracking. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_50
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DOI: https://doi.org/10.1007/11732242_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33237-4
Online ISBN: 978-3-540-33238-1
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