Discriminating features learning in hand gesture classification

作者：Jiang Feng; Wang Cuihua^*; Gao Yang; Wu Shen; Zhao Debin

来源：IET Computer Vision, 2015, 9(5): 673-680.

DOI：10.1049/iet-cvi.2014.0426

• Discriminative ability
• Features extraction
• Hand-gesture recognition
• Histogram of oriented gradient features
• Local binary patterns
• Red , green and blues
• Structure features
• Subspace projection

The advent and popularity of Kinect provides a new choice and opportunity for hand gesture recognition (HGR) research. In this study, the authors propose a discriminating features extraction for HGR, in which features from red, green and blue (RGB) images and depth images are both explored. More specifically, histogram of oriented gradient feature, local binary pattern feature, structure feature and three-dimensional voxel feature are first extracted from RGB images and depth images, then these features are further reduced with a novel deflation orthogonal discriminant analysis, which enhances the discriminative ability of the features with supervised subspace projection. The extensive experimental results show that the proposed method improves the HGR performance significantly.

• 出版日期2015-10
• 单位哈尔滨工业大学