A novel feature extracting method for dynamic gesture recognition based on support vector machine

Author

Yuanrong Xu ; Qianqian Wang ; Xiao Bai ; Yen-Lun Chen ; Xinyu Wu

Author_Institution

Shenzhen Key Lab. for Comput. Vision & Pattern Recognition, Shenzhen Inst. of Adv. Technol., Shenzhen, China

fYear

2014

fDate

28-30 July 2014

Firstpage

437

Lastpage

441

Abstract

In this paper, we propose a method based on the SVM algorithm to recognize dynamic hand gestures. The information of motion trajectory is captured by a leap motion in three-dimension space. A new methodology of feature extracting is proposed to guarantee the length of samples being the same. The elements of feature vectors are ranged according to two different criteria: one is the amplitude of the variation of orientation angles, and the other criterion is the order of the appearance of features. Experimental results show that this method can classify the dynamic hand gestures effectively.

Keywords

feature extraction; gesture recognition; image classification; image motion analysis; support vector machines; SVM algorithm; dynamic gesture recognition; dynamic hand gesture classification; dynamic hand gesture recognition; feature extracting method; motion trajectory; support vector machine; Automation; Equations; Feature extraction; Hidden Markov models; Mathematical model; Trajectory; Vectors; 3D trajectory; SVM; gesture recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Automation (ICIA), 2014 IEEE International Conference on

Conference_Location

Hailar

Type

conf

DOI

10.1109/ICInfA.2014.6932695

Filename

6932695