Detecting hands in video images using scale invariant local descriptors

Authors:
Jan Richarz;Thomas Plötz;Gernot A. Fink
Affiliations:
University of Dortmund, Dortmund, Germany;University of Dortmund, Dortmund, Germany;University of Dortmund, Dortmund, Germany
Venue:
VIIP '07 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing
Year:
2007

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Abstract

In this paper, we describe our approach on hand detection in cluttered images using scale invariant features. We claim that, while modelling hands as a whole is bound to fail because of their strongly articulated nature, treating them as a collection of weakly connected characteristic regions seems promising. Different approaches to finding and robustly modelling such regions - or local object descriptors - invariantly to scale and orientation of the object in question have been proposed. As an example, we demonstrate our approach using the well-known scale-invariant feature transform (SIFT), combined with a region-based postprocessing to eliminate false positives. We present detailed results on a large set of images from a realistic interaction scenario with a smart room.