Book Chapter Details
Mandatory Fields
Kelly, D;McDonald, J;Markham, C
2011 January
MACHINE LEARNING FOR VISION-BASED MOTION ANALYSIS: THEORY AND TECHNIQUES
Recognition of Spatiotemporal Gestures in Sign Language Using Gesture Threshold HMMs
SPRINGER-VERLAG LONDON LTD
GODALMING
Published
1
Optional Fields
In this paper, we propose a framework for the automatic recognition of spatiotemporal gestures in Sign Language. We implement an extension to the standard HMM model to develop a gesture threshold HMM (GT-HMM) framework which is specifically designed to identify inter gesture transitions. We evaluate the performance of this system, and different CRF systems, when recognizing gestures and identifying inter gesture transitions. The evaluation of the system included testing the performance of conditional random fields (CRF), hidden CRF (HCRF) and latent-dynamic CRF (LDCRF) based systems and comparing these to our GT-HMM based system when recognizing motion gestures and identifying inter gesture transitions.
1617-7916
307
348
10.1007/978-0-85729-057-1_12
Grant Details