With the growing usage of computer systems in daily life, a natural and intuitive Human Computer Interaction (HCI) method to support the embedding of computer systems in our environment seems necessary. Gestures are of utmost importance for the design of natural user interfaces. Hand gesture recognition to extract meaningful expressions from the human hand movements and postures is being used for different applications. However, the recognition of hand gestures that contain different hand poses can be challenging. In this paper, we propose a system (called HANDY) for hand gesture recognition that is flexible to be trained to recognize a variety of user-defined gestures defined as sequences of static hand postures. The system has been designed to be used in uncontrolled environments, to handle dynamic and cluttered backgrounds, and without the need of using any wearable sensor or any specific clothing. Evaluation results show a good average accuracy in gesture recognition.

HANDY: A Configurable Gesture Recognition System

TEIMOURIKIA, MAHSA;SAIDINEJAD, HASSAN;COMAI, SARA
2014-01-01

Abstract

With the growing usage of computer systems in daily life, a natural and intuitive Human Computer Interaction (HCI) method to support the embedding of computer systems in our environment seems necessary. Gestures are of utmost importance for the design of natural user interfaces. Hand gesture recognition to extract meaningful expressions from the human hand movements and postures is being used for different applications. However, the recognition of hand gestures that contain different hand poses can be challenging. In this paper, we propose a system (called HANDY) for hand gesture recognition that is flexible to be trained to recognize a variety of user-defined gestures defined as sequences of static hand postures. The system has been designed to be used in uncontrolled environments, to handle dynamic and cluttered backgrounds, and without the need of using any wearable sensor or any specific clothing. Evaluation results show a good average accuracy in gesture recognition.
2014
ACHI 2014, The Seventh International Conference on Advances in Computer-Human Interactions
9781612083254
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/823131
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