[1]JIA Heming,ZHU Chuanxu,ZHANG Sen,et al.Research on gesture recognition and classification of dual-tree complex wavelet and spatial information[J].CAAI Transactions on Intelligent Systems,2018,13(4):619-624.[doi:10.11992/tis.201708003]
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Research on gesture recognition and classification of dual-tree complex wavelet and spatial information

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 13 Number of periods: 2018 4 Page number: 619-624 Column: 学术论文—机器感知与模式识别 Public date: 2018-07-05
Title:
Research on gesture recognition and classification of dual-tree complex wavelet and spatial information
Author(s):
JIA Heming1;  ZHU Chuanxu1;  ZHANG Sen1;  YANG Zewen2;  HE Dongxu2
1. College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China;
2. College of Automation, Harbin Engineering University, Harbin 150001, China
Keywords:
gesture recognition; spatial feature; dual-tree complex wavelet; feature fusion; classifier optimization; BD-SVM; radial basis kernel function; static test
CLC:
TP273
DOI:
10.11992/tis.201708003
Abstract:
To improve the validity of features obtained in gesture recognition, in this paper, we propose a fusion feature that combines spatial and dual-tree complex wavelet transform features. These features mainly include seven components (horizontal position, vertical position, aspect ratio, rectangular degree, Hu moments, etc.) and 27 dimensional features, comprising 11 dimensional spatial features and 16 dimensional dual-tree complex wavelet transform features. We employ the optimal distance support vector machine (BD-SVM) classification method to optimize training samples for the classifier optimization algorithm. The experimental results show that, in a test of gestures “1~9” using the RBF kernel function, the highest average recognition accuracy is 90.33% and the average recognition time is 0.026 s. These results reveal that the proposed method demonstrates excellent static gesture recognition, a high training speed, and accuracy in identification.
References:
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