Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/17856
Title: Fast and accurate hand pose detection for human-robot interaction
Authors: Antón Canalís, Luis
Sánchez Nielsen, Elena
Castrillón-Santana, Modesto 
UNESCO Clasification: 120304 Inteligencia artificial
Issue Date: 2005
Journal: Lecture Notes in Computer Science 
Abstract: Enabling natural human-robot interaction using computer vision based applications requires fast and accurate hand detection. However, previous works in this field assume different constraints, like a limitation in the number of detected gestures, because hands are highly complex objects difficult to locate. This paper presents an approach which integrates temporal coherence cues and hand detection based on wrists using a cascade classifier. With this approach, we introduce three main contributions: (1) a transparent initialization mechanism without user participation for segmenting hands independently of their gesture, (2) a larger number of detected gestures as well as a faster training phase than previous cascade classifier based methods and (3) near real-time performance for hand pose detection in video streams.
URI: http://hdl.handle.net/10553/17856
ISBN: 3-540-26153-2
ISSN: 0302-9743
DOI: 10.1007/11492429_67

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10.1007/11492429_67

Source: Lecture Notes in Computer Science[ISSN 0302-9743],v. 3522, p. 553-560
Appears in Collections:Actas de congresos
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