Static Hand Gesture Recognition for PowerPoint Presentation Navigation using Thinning Method

In this paper a method to control the power point presentation navigation using bare hands, is proposed. The proposed method takes static hand gestures as input via webcam connected to the computerand uses thinning method to obtain the hand shape parameters. Thesehand shape parameters are used to countthe number of raised fingers. Based on this count, the gestures are identified and then used to control the slides. This method does not require devices such asmarkers orgloves or any other devices andalso does not require any database to identify a gesture

A Depth-based approach for 3D dynamic gesture recognition

International audienceIn this paper we propose a recognition technique of 3D dynamic gesture for human robot interaction (HRI)based on depth information provided by Kinect sensor. The body is tracked using the skeleton algorithm providedby the Kinect SDK. The main idea of this work is to compute the angles of the upper body joints whichare active when executing gesture. The variation of these angles are used as inputs of Hidden Markov Models(HMM) in order to recognize the dynamic gestures. Results demonstrate the robustness of our method againstenvironmental conditions such as illumination changes and scene complexity due to using depth informationonl