Consumer electronics control system based on hand gesture moment invariants

Almost all consumer electronic equipment today uses remote controls for user interfaces. However, the variety of physical shapes and functional commands that each remote control features also raises numerous problems: the difficulties in locating the required remote control, the confusion with the button layout, the replacement issue and so on. The consumer electronics control system using hand gestures is a new innovative user interface that resolves the complications of using numerous remote controls for domestic appliances. Based on one unified set of hand gestures, this system interprets the user hand gestures into pre-defined commands to control one or many devices simultaneously. The system has been tested and verified under both incandescent and fluorescent lighting conditions. The experimental results are very encouraging as the system produces real-time responses and highly accurate recognition towards various gestures.

[1]  Sumita Pennathur,et al.  Face Detection Using Color Thresholding , and Eigenimage Template Matching , 2003 .

[2]  Collin Wang,et al.  A virtual end-effector pointing system in point-and-direct robotics for inspection of surface flaws using a neural network based skeleton transform , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[3]  Yoshiaki Shirai,et al.  Gesture based human-robot interaction using a frame based software platform , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[4]  Patrick van der Smagt,et al.  Introduction to neural networks , 1995, The Lancet.

[5]  Simon Haykin,et al.  Neural networks , 1994 .

[6]  Christoph Maggioni,et al.  A novel gestural input device for virtual reality , 1993, Proceedings of IEEE Virtual Reality Annual International Symposium.

[7]  Laurene V. Fausett,et al.  Fundamentals Of Neural Networks , 1993 .

[8]  Tieniu Tan,et al.  Gesture recognition using temporal template based trajectories , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[9]  David Zeltzer,et al.  A survey of glove-based input , 1994, IEEE Computer Graphics and Applications.

[10]  Tosiyasu L. Kunii,et al.  Model-based analysis of hand posture , 1995, IEEE Computer Graphics and Applications.

[11]  D. L. Quam,et al.  Gesture recognition with a DataGlove , 1990, IEEE Conference on Aerospace and Electronics.

[12]  Qian Zhongliang,et al.  Automatic ship classification by superstructure moment invariants and two-stage classifier , 1992, [Proceedings] Singapore ICCS/ISITA `92.

[13]  Michel Beaudouin-Lafon,et al.  Charade: remote control of objects using free-hand gestures , 1993, CACM.

[14]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .

[15]  Young-Kiu Choi,et al.  Recognition of hand gesture to human-computer interaction , 2000, 2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies.

[16]  Yoshiaki Shirai,et al.  Vision-based human interface with user-centered frame , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[17]  Geoffrey E. Hinton,et al.  Glove-Talk: a neural network interface between a data-glove and a speech synthesizer , 1993, IEEE Trans. Neural Networks.

[18]  Roberto Cipolla,et al.  Robust structure from motion using motion parallax , 1993, 1993 (4th) International Conference on Computer Vision.

[19]  Björn W. Schuller,et al.  A real-time system for hand gesture controlled operation of in-car devices , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

[20]  Mubarak Shah,et al.  Recognizing Hand Gestures , 1994, ECCV.