Behavior Recognition Combining Regional Optical Flow Features and Temporal Templates

Authors

Manyi Wang, Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China;
Yaling Song, Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China;
Li Yu, Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China;
Zhang Liang, Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China;

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.

Recommended Citation

Wang, Manyi; Song, Yaling; Yu, Li; and Liang, Zhang (2020) "Behavior Recognition Combining Regional Optical Flow Features and Temporal Templates," Journal of System Simulation: Vol. 27: Iss. 5, Article 32.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss5/32

First Page

1146

Revised Date

2014-08-04

DOI Link

https://doi.org/

Last Page

1151

CLC

TP391

Recommended Citation

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.