Title :
Recognising moving hand shapes
Author :
Holden, Eun-Jung ; Owens, Robyn
Author_Institution :
Sch. of Comput. Sci. & Software Eng., Univ. of Western Australia, Crawley, WA, Australia
Abstract :
The paper presents a new hand shape representation technique that characterises the finger-only topology of the hand, by adapting an existing technique from speech signal processing. From a moving hand sequence, the tracking algorithm determines the centre of the largest convex subset of the hand, using a combination of pattern matching and condensation algorithms. A hand shape feature represents the topological formation of the finger-only regions of the hand using a linear predictive coding parameter set called cepstral coefficients. Experimental results demonstrate the effectiveness of detecting the shape feature from motion sequences.
Keywords :
feature extraction; gesture recognition; image motion analysis; image sequences; linear predictive coding; object recognition; optical tracking; pattern matching; topology; cepstral coefficients; condensation algorithm; convex subset; finger-only topology; hand gesture recognition; hand shape representation; linear predictive coding parameter set; motion sequences; moving hand shape recognition; pattern matching; shape feature detection; speech signal processing; tracking algorithm; Autocorrelation; Cepstral analysis; Feature extraction; Linear predictive coding; Pattern matching; Pixel; Shape; Signal processing algorithms; Speech recognition; Topology;
Conference_Titel :
Image Analysis and Processing, 2003.Proceedings. 12th International Conference on
Print_ISBN :
0-7695-1948-2
DOI :
10.1109/ICIAP.2003.1234018