Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/17652
Title: Hand pose detection for vision-based gesture interfaces
Authors: Antón Canalís, Luis
Sánchez Nielsen, Elena
Castrillón-Santana, M. 
UNESCO Clasification: 120304 Inteligencia artificial
Issue Date: 2005
Journal: Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005
Abstract: Vision-based applications designed for humanmachine interaction require fast and accurate hand detection. However, previous works on this field assume different constraints, like a limitation in the number of detected gestures, because hands are highly complex objects to locate. This paper presents an approach which changes the detection target without limiting the number of detected gestures. Using a cascade classifier we detect hands based on their wrists. With this approach, we introduce two main contributions: (1) a reliable segmentation, independently of the gesture being made and (2) a training phase faster than previous cascade classifier based methods. The paper includes experimental evaluations with different video streams that illustrate the efficiency and suitability for perceptual interfaces.
URI: http://hdl.handle.net/10553/17652
Source: Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005, p. 506-509
Appears in Collections:Actas de congresos
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