Fast and accurate hand pose detection for human-robot interaction
Data(s) |
15/07/2016
15/07/2016
2005
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Resumo |
<p>[EN]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.</p> |
Identificador |
http://hdl.handle.net/10553/17856 728053 <p><a href="http://dx.doi.org/10.1007/11492429_67" target="_blank">10.1007/11492429_67</a></p> |
Idioma(s) |
eng |
Direitos |
info:eu-repo/semantics/openAccess |
Fonte |
<p>Pattern Recognition and Image Analysis. Berlin: Springer, 2005 (Lecture Notes in Computer Science, ISSN 0302-9743; vol. 3522; pp 553-560). ISBN 978-3-540-26153-7. ISBN on-line 978-3-540-32237-5</p> |
Palavras-Chave | #120304 Inteligencia artificial |
Tipo |
info:eu-repo/semantics/conferenceObject |