Abstract
As the accuracy of standard Harris algorithm is not high in the application of behavior recognition, this paper proposed a behavior recognition model based on scale adaptive local spatio-temporal characteristics Harris algorithm, which firstly uses local spatio-temporal characteristics function to achieve fast convolution in order to reduce complexity of the algorithm, and then uses scale adaptive local spatio-temporal characteristics function to replace Gaussian function as the filter of the algorithm, and finally calculates the adaptive matrix and the response value of the angle points in order to improve the accuracy of behavior recognition. Simulation results show that the accuracy of the Harris Algorithm based on scale adaptive local spatio-temporal characteristics, proposed in this paper, is higher than the standard Harris algorithm on behavior recognition.
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Acknowledgments
This work was supported by the Education of Zhejiang Province (Grant No. Y201225667), the Department of Science and Technology of Zhejiang Province (Grant No. 2014C31065), and the Department of Science and Technology of Zhejiang Province (Grant No. 2015C31091).
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Xu, Z., Li, X., Wu, F., Hu, F., Wu, L. (2017). Behavior Recognition of Scale Adaptive Local Spatio-Temporal Characteristics Harris Algorithm . In: Balas, V., Jain, L., Zhao, X. (eds) Information Technology and Intelligent Transportation Systems. Advances in Intelligent Systems and Computing, vol 454. Springer, Cham. https://doi.org/10.1007/978-3-319-38789-5_37
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DOI: https://doi.org/10.1007/978-3-319-38789-5_37
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