A real-time hand gesture recognition method

This paper presents a real-time hand gesture recognition method. Hand regions are located by combining adaptive skin color detection and motion detection. Histograms of oriented gradients (HOG) are used to describe hand image. Extracted HOG features are projected into low-dimensional subspace using PCA-LDA (Principle Component Analysis and Linear Discriminant Analysis). And then distances between the projected features and each gesture class center are calculated. Finally the recognition results are obtained by the nearest neighbor method. Experimental results showed that the proposed method gained detection rate up to 91% with real-time performance.