Title :
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
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;
Conference_Titel :
Information and Automation (ICIA), 2014 IEEE International Conference on
Conference_Location :
Hailar
DOI :
10.1109/ICInfA.2014.6932695
