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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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