Face-Based Perceptual Interface for Computer- Human interaction

Nowadays accessibility to new technologies for everyone is a task to accomplish. A way to contribute to this aim is creating new interfaces based on computer vision using low cost devices such as webcams. In this paper a face-based perceptual user interface is presented. Our approach is divided in four steps: automatic face detection, best face features detection, feature tracking and face gesture recognition. Using facial feature tracking and face gesture recognition it is possible to replace the mouse’s motion and its events. This goal implies the restriction of real-time response and the use of unconstrained environments. Finally, this application has been tested successfully on disabled people with problems in hands or arms that can not use the traditional interfaces such as a mouse or a keyboard.

[1]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[2]  D. Ullyot Look ma, no hands! , 1996, The Annals of thoracic surgery.

[3]  M. Betke,et al.  The Camera Mouse: visual tracking of body features to provide computer access for people with severe disabilities , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[4]  Mark W. Newman,et al.  Informal PUIs: No Recognition Required , 2002 .

[5]  Kentaro Toyama,et al.  “Look, Ma – No Hands!” Hands-Free Cursor Control with Real-Time 3D Face Tracking , 1998 .

[6]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[7]  Dmitry O. Gorodnichy Nouse ‘Use Your Nose as a Mouse’ – a New Technology for Hands-free Games and Interfaces , 2002 .

[8]  Gerhard Roth,et al.  Nouse 'Use Your Nose as a Mouse' - a New Technology for Hands-free Games and Interfaces , 2002 .

[9]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[10]  Simon Baker,et al.  Lucas-Kanade 20 Years On: A Unifying Framework , 2004, International Journal of Computer Vision.