Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
GestureWrist and GesturePad: Unobtrusive Wearable Interaction Devices
ISWC '01 Proceedings of the 5th IEEE International Symposium on Wearable Computers
A Review on Vision-Based Full DOF Hand Motion Estimation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
iRing: intelligent ring using infrared reflection
Proceedings of the 25th annual ACM symposium on User interface software and technology
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In this paper, we describe a novel sensor device which recognizes hand shapes using wrist contours. Although hand shapes can express various meanings with small gestures, utilization of hand shapes as an interface is rare in domestic use. That is because a concise recognition method has not been established. To recognize hand shapes anywhere with no stress on the user, we developed a wearable wrist contour sensor device and a recognition system. In the system, features, such as sum of gaps, were extracted from wrist contours. We conducted a classification test of eight hand shapes, and realized approximately 70% classification rate.