Abstract
The identification of human activity in video, for example whether a person is walking, clapping, waving, etc. is extremely important for video interpretation. Since different people would perform the same action across different number of frames, matching training and test actions is not a trivial task. In this paper we discuss a new technique for video shot matching where the shots matched are of different sizes. The proposed technique is based on frequency domain analysis of feature data and it is shown to achieve very high recognition accuracy on a number of different human actions with synthetic data and real life data.
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© 2004 Springer-Verlag Berlin Heidelberg
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Wang, J.J., Singh, S. (2004). Video Based Human Behavior Identification Using Frequency Domain Analysis. In: Yang, Z.R., Yin, H., Everson, R.M. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2004. IDEAL 2004. Lecture Notes in Computer Science, vol 3177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28651-6_32
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DOI: https://doi.org/10.1007/978-3-540-28651-6_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22881-3
Online ISBN: 978-3-540-28651-6
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