Dynamic gesture recognition based on improved DTW algorithm

Author

Xiaogang Ruan ; Chongyang Tian

Author_Institution

Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China

fYear

2015

fDate

2-5 Aug. 2015

Firstpage

2134

Lastpage

2138

Abstract

This paper aims at a dynamic gesture recognition method based on the improved DTW algorithm. Firstly, the 3D position of human skeletal points is obtained through the analysis of the depth information, which is obtained by SDK of the Kinect sensor. 8 points are selected as the hand movement characteristics, and the mathematical model of the gesture is established by the method of weighted distance. Then the DTW algorithm is improved by distortion threshold and the path constraints, which is used for training templates and dynamic gesture recognition. The results show that this method can realize the dynamic gesture recognition and have a good real-time performance and robustness. At the same time, the improved DTW algorithm has great improvement in speed and accuracy.

Keywords

gesture recognition; image sensors; Kinect sensor; depth information; distortion threshold; dynamic gesture recognition; dynamic time warping algorithm; hand movement characteristics; human skeletal points; improved DTW algorithm; path constraints; weighted distance method; Algorithm design and analysis; Distortion; Gesture recognition; Heuristic algorithms; Libraries; Robustness; Time series analysis; Dynamic gesture recognition; Improved DTW algorithm; Kinect sensor;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics and Automation (ICMA), 2015 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4799-7097-1

Type

conf

DOI

10.1109/ICMA.2015.7237816

Filename

7237816