Vision-based Hand Gesture Recognition Technology

Abstract

Human-computer interaction has a wide range of application prospects in many fields such as medicine, entertainment, industry and education. Gesture recognition is one of the most important technologies for gesture interaction between humans and robots, and visual gesture recognition increases the user's comfort and freedom compared with data glove recognition. This paper summarizes the general process of visual gesture recognition based on the literature, including three steps: pre-processing, feature extraction, and gesture classification. It also defines static and dynamic gestures and makes a comparison between their differences and recognition emphases. Based on static and dynamic gesture recognition, this paper summarizes the commonly - used visual gesture recognition methods. For static gesture recognition, it includes methods such as the template - matching method and the AdaBoost - based method. As for dynamic gesture recognition, it encompasses methods like the hidden Markov model method and the dynamic time regularization method. Finally, some applications of visual gesture recognition are introduced, for example, a non-contact system for operating rooms and smart home control.