DocumentCode :
2510641
Title :
Hand Pointing Estimation for Human Computer Interaction Based on Two Orthogonal-Views
Author :
Hu, Kaoning ; Canavan, Shaun ; Yin, Lijun
Author_Institution :
Dept. of Comput. Sci., State Univ. of New York at Binghamton, Binghamton, NY, USA
fYear :
2010
fDate :
23-26 Aug. 2010
Firstpage :
3760
Lastpage :
3763
Abstract :
Hand pointing has been an intuitive gesture for human interaction with computers. Big challenges are still posted for accurate estimation of finger pointing direction in a 3D space. In this paper, we present a novel hand pointing estimation system based on two regular cameras, which includes hand region detection, hand finger estimation, two views´ feature detection, and 3D pointing direction estimation. Based on the idea of binary pattern face detector, we extend the work to hand detection, in which a polar coordinate system is proposed to represent the hand region, and achieved a good result in terms of the robustness to hand orientation variation. To estimate the pointing direction, we applied an AAM based approach to detect and track 14 feature points along the hand contour from a top view and a side view. Combining two views of the hand features, the 3D pointing direction is estimated. The experiments have demonstrated the feasibility of the system.
Keywords :
gesture recognition; human computer interaction; 3D pointing direction estimation; active appearance model; binary pattern face detector; feature detection; hand finger estimation; hand gesture; hand pointing estimation; hand region detection; human computer interaction; orthogonal-views; polar coordinate system; Detectors; Estimation; Feature extraction; Fingers; Shape; Three dimensional displays; Wrist;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
ISSN :
1051-4651
Print_ISBN :
978-1-4244-7542-1
Type :
conf
DOI :
10.1109/ICPR.2010.916
Filename :
5597569
Link To Document :
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