Real-time hand gesture feature extraction using depth data

In this paper, a novel method is proposed to extract hand gesture features in real-time from RGB-D images captured by the Microsoft´s Kinect. A contour length information based de-noise method is introduced for the hand gesture smooth segmentation and edge contour extraction. In addition, a finger earth mover´s distance algorithm is applied with a novel approach to locate the palm image and extract fingertip features. Especially the proposed Lasso algorithm can effectively extract the fingertip feature from a hand contour curve correctly with excellent real-time performance.