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FGR
2002
IEEE

Hand Gesture Recognition using Multi-Scale Colour Features, Hierarchical Models and Particle Filtering

13 years 8 months ago
Hand Gesture Recognition using Multi-Scale Colour Features, Hierarchical Models and Particle Filtering
This paper presents algorithms and a prototype system for hand tracking and hand posture recognition. Hand postures are represented in terms of hierarchies of multi-scale colour image features at different scales, with qualitative inter-relations in terms of scale, position and orientation. In each image, detection of multi-scale colour features is performed. Hand states are then simultaneously detected and tracked using particle filtering, with an extension of layered sampling referred to as hierarchical layered sampling. Experiments are presented showing that the performance of the system is substantially improved by performing feature detection in colour space and including a prior with respect to skin colour. These components have been integrated into a real-time prototype system, applied to a test problem of controlling consumer electronics using hand gestures. In a simplified demo scenario, this system has been successfully
Lars Bretzner, Ivan Laptev, Tony Lindeberg
Added 14 Jul 2010
Updated 14 Jul 2010
Type Conference
Year 2002
Where FGR
Authors Lars Bretzner, Ivan Laptev, Tony Lindeberg
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