Real time hand shape recognition for man-machine interfaces

The authors describe a hand shape recognition method for man-machine interfaces using a pipeline image processor. The basic strategy is to use simple but effective real-time dynamical image processing to enhance the reliability of hand shape recognition. Low-level image processing reduces the data required for recognition of a hand shape. An algorithm for a noncontact-type hand shape recognizer has been developed for incorporation into a virtual reality environment. To realize this recognizer, the most important considerations are processing speed, the pointer's positional accuracy, and command recognition rate. The usefulness of the proposed method is verified through experimental results for these three points.<<ETX>>

[1]  Warren Robinett,et al.  Virtual environment display system , 1987, I3D '86.

[2]  Demetri Terzopoulos,et al.  Energy Constraints on Deformable Models: Recovering Shape and Non-Rigid Motion , 1987, AAAI.

[3]  Hiroshi Harashima,et al.  Intelligent Image Coding and Communications with Realistic Sensations --Recent Trends-- , 1991 .

[4]  Alex Pentland,et al.  Recovery of Nonrigid Motion and Structure , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Fumio Kishino,et al.  Real time hand shape recognition using pipe-line image processor , 1992, [1992] Proceedings IEEE International Workshop on Robot and Human Communication.

[6]  Steven D. Pieper,et al.  Hands-on interaction with virtual environments , 1989, UIST '89.

[7]  F. P. Brooks,et al.  Grasping reality through illusion—interactive graphics serving science , 1988, CHI '88.

[8]  Alex Pentland,et al.  Recovery of non-rigid motion and structure , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  F. Raab,et al.  Magnetic Position and Orientation Tracking System , 1979, IEEE Transactions on Aerospace and Electronic Systems.