A novel hand gesture input device based on inertial sensing technique

In this paper, we present a novel gesture-based input device by using inertial sensing technique. The trajectories of user's hand-drawn gestures in 3D space are captured and recognized by this device to fulfill user interaction task. The proposed device employs gyro-free inertial measurement unit (IMU) to track hand motions without requiring any external reference sensors or signals. Since the unbounded growing error of trajectory estimation, as a major drawback of IMU-based motion tracking technology, is carefully solved by using zero velocity compensation. Here, a deliberately-designed motion detection scheme is proposed to capture accurate hand motion period. Finally, the recognition algorithm based on Bayesian networks takes estimated trajectories and finds the corresponding gesture model with the maximum probability. Because the IMU provides outstanding capability of self-contained positioning, the proposed device is extraordinary simple and effective, comparing with the devices using other tracking technologies such as vision-based system. Experimental results also show its effectiveness and feasibility. Currently, after employing the trajectory estimation method provided in this paper, the recognition rate of 95.51% for 14 gestures has been achieved when this device is implemented as a TV remote controller. It can be used as a powerful, flexible interface for ubiquitous computing device.

[1]  Jing Yang,et al.  Development of the gyro-free handwriting input device based on inertial navigation system (INS) theory , 2004, SICE 2004 Annual Conference.

[2]  Sung-Jung Cho,et al.  Bayesian network modeling of strokes and their relationships for on-line handwriting recognition , 2004, Pattern Recognit..

[3]  Vladimir Pavlovic,et al.  Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Jing Yang,et al.  Analysis and compensation of errors in the input device based on inertial sensors , 2004, International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004..

[5]  Mohinder S. Grewal,et al.  Global Positioning Systems, Inertial Navigation, and Integration , 2000 .

[6]  Tamás Szirányi,et al.  Supervised training based hand gesture recognition system , 2002, Object recognition supported by user interaction for service robots.

[7]  Kazunori Itoh,et al.  Handwritten Pattern Reproduction Using 3D Inertial Measurement of Handwriting Movement , 2002 .

[8]  Tsukasa Ogasawara,et al.  A hand-pose estimation for vision-based human interfaces , 2003, IEEE Trans. Ind. Electron..

[9]  Jing Yang,et al.  A miniaturized attitude estimation system for a gesture-based input device with fuzzy logic approach , 2003 .

[10]  Gi-Joon Nam,et al.  Two-dimensional position deteciton system with MEMS accelerometer for MOUSE applications , 2001, DAC '01.

[11]  P. Varaiya,et al.  Design of gyroscope-free navigation systems , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[12]  Kyoung-Ho Kang,et al.  Self-contained spatial input device for wearable computers , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..

[13]  J. Chae,et al.  Two-dimensional position detection system with MEMS accelerometer for mouse applications , 2001, Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232).