The use of hand gestures provides an attractive alternative to cumbersome interface devices for human-computer interaction (HCI). In particular, visual interpretation of hand gestures can help in achieving the ease and naturalness desired for HCI. We survey the literature on vision-based hand gesture recognition within the context of its role in HCI. The number of approaches to video-based hand gesture recognition has grown in recent years. Thus, the need for systematization and analysis of di erent aspects of gestural interaction has developed. We discuss a complete model of hand gestures that possesses both spatial and dynamic properties of human hand gestures and can accommodate for all their natural types. Two classes of models that have been employed for interpretation of hand gestures for HCI are considered. The rst utilizes 3D models of the human hand, while the second relies on the appearance of the human hand in the image. Investigation of model parameters and analysis features and their impact on the interpretation of hand gestures is presented in the light of the naturalness desired for HCI. 3D hand models o er a way for complete modeling of all hand gestures. However, they lack the simplicity and computational e ciency which is highly preferred, and currently feasible with the appearance-based models. We suggest some methods that can increase the e ectiveness of gestural interface for HCI. Integration of hand gestures with other natural modes of communication can provide a potential answer to this problem. Nonetheless, further work that puts together advances in computer vision with understanding of human-computer interaction will be necessary to produce an e ective and natural hand gesture interface.
For a comprehensive overview of hand-gesture recognition we refer to REF .
Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Science