Computer Science ›› 2018, Vol. 45 ›› Issue (8): 22-27.doi: 10.11896/j.issn.1002-137X.2018.08.005

• ChinaMM 2017 • Previous Articles     Next Articles

Human Action Recognition Framework with RGB-D Features Fusion

MAO Xia1, WANG Lan1, LI Jian-jun1,2   

  1. School of Electronic and Information Engineering,Beihang University,Beijing 100191,China1
    School of Information Engineering,Inner Mongolia University of Science and Technology,Baotou,Inner Mongolia 014010,China2
  • Received:2017-10-24 Online:2018-08-29 Published:2018-08-29

Abstract: Human action recognition is an important research direction in the field of computer vision and pattern recognition.The complexity of human behavior and the variety of action performing make behavior recognition still as a challenging subject.With the new generation of sensing technology,RGB-D cameras can simultaneously record RGB images,depth images,and extract skeleton information from depth images in real time.How to take advantages of above information has become the new hotspot and breakthrough point of behavior recognition research.This paper presented a new feature extraction method based on Gaussian weighted pyramid histograms of orientation gradients for RGB images,and built an action recognition framework fusing multiple features.The feature extraction method and the framework proposed in this paper were researched on three databases:UTKinect-Action3D,MSR-Action 3D and Florence 3D Actions.The results indicate that the proposed action recognition framework achieves the accuracy of 97.5%,93.1%,91.7% respectively.It shows the effectiveness of the proposed action recognition framework.

Key words: Action recognition, Feature fusion, Gaussian weighted, Histogram of orientation gradients, Sparse representation classifier

CLC Number: 

  • TP391
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