Kelly, Daniel and McDonald, John and Markham, Charles (2009) Evaluation of Threshold Model HMMs and Conditional Random Fields for Recognition of Spatiotemporal Gestures in Sign Language. In: IEEE 12th International Conference on Computer Vision Workshops (ICCV Workshops), 2009. IEEE, pp. 490-497. ISBN 9781424444427

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Abstract

In this paper we evaluate the performance of Conditional Random Fields (CRF) and Hidden Markov Models when recognizing motion based gestures in sign language. We implement CRF, Hidden CRF and Latent-Dynamic CRF based systems and compare these to a HMM based system when recognizing motion gestures and identifying inter gesture transitions. We implement a extension to the standard HMM model to develop a threshold HMM framework which is specifically designed to identify inter gesture transitions. We evaluate the performance of this system, and the different CRF systems, when recognizing gestures and identifying inter gesture transitions.

Item Type:	Book Section
Keywords:	hidden Markov models; gesture recognition; Threshold Model HMMs; Conditional Random Fields; Spatiotemporal Gestures; Sign Language;
Academic Unit:	Faculty of Science and Engineering > Computer Science
Item ID:	8339
Identification Number:	https://doi.org/10.1109/ICCVW.2009.5457660
Depositing User:	John McDonald
Date Deposited:	15 Jun 2017 15:57
Publisher:	IEEE
Refereed:	Yes
URI:	http://ieeexplore.ieee.org
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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