Behavior Recognition Combining Regional Optical Flow Features and Temporal Templates

Abstract

Abstract: A method was proposed to recognize human behavior, which combined the wavelet moments of temporal templates and the speed feature by optical flow. The wavelet moments are not only rotation, translation and scale invariance, but also have the multi-scale characteristics of wavelet. The shape feature of the motion history image and motion energy image can be described. To simple motions, it's effectively, but it can't present the speed information. Regional optical flow was calculated to describe the direction and amplitude features of motion by Lucas-Kanade algorithm. It could make up shortcomings of wavelet moment without speed information. Being combined two ways of describing the motion and based on the Weizmann Database, experiment results verify the proposed method effectiveness.

Key words: human behavior recognition, temporal templates, wavelet moment, calculation of optical flow

CLC Number:

TP391

Wang Manyi, Song Yaling, Li Yu, Zhang Liang. Behavior Recognition Combining Regional Optical Flow Features and Temporal Templates[J]. Journal of System Simulation, 2015, 27(5): 1146-1151.

References

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