Open AccessHuman action recognition based on Kinect
Author(s) -
Jiahui An,
Xinbin Cheng,
Qing Wang,
Chen Hong,
Jiayue Li,
Shiji Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1693/1/012190
Subject(s) - action recognition , computer science , support vector machine , artificial intelligence , classifier (uml) , human skeleton , pattern recognition (psychology) , skeleton (computer programming) , action (physics) , activity recognition , computer vision , class (philosophy) , physics , quantum mechanics , programming language
With the emergence of Kinect, many research results have emerged in human action recognition based on skeleton information, which has promoted the development of human-computer interaction. In this paper, from the skeleton data obtained by Kinect, static features and dynamic features are extracted, and the two are merged; SVM classifier is used for action recognition. It is verified on the MSR Daily Activity 3D data set, and the experimental results show that the method in this paper improves the accuracy of action recognition.