Fast and accurate hand pose detection for human-robot interaction

Authors:
Luis Antón-Canalís;Elena Sánchez-Nielsen;Modesto Castrillón-Santana
Affiliations:
Institute of Intelligent Systems and Numerical Applications in Engineering, Campus Universitario de Tafira, Gran Canaria, Spain;Department of S.O.R. and Computation, University of La Laguna, Spain;Institute of Intelligent Systems and Numerical Applications in Engineering, Campus Universitario de Tafira, Gran Canaria, Spain
Venue:
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
Year:
2005

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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.