Papiez, Bartek, Matuszewski, Bogdan, Shark, Lik and Quan, Wei (2013) Facial Expression Recognition using Diffeomorphic Image Registration Framework. In: Mathematical Methodologies in Pattern Recognition and Machine Learning. Springer Proceedings in Mathematics & Statistics, 30 (2013). Springer Verlag, New York, NY, USA, pp. 179-194. ISBN 978-1-4614-5075-7
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Official URL: http://dx.doi.org/10.1007/978-1-4614-5076-4_12
This paper presents a new method for facial expression modelling and recognition based on diffeomorphic image registration parameterised via stationary velocity fields in the log-Euclidean framework. The validation and comparison are done using different statistical shape models (SSM) built using the Point Distribution Model (PDM), velocity fields and deformation fields. The obtained results show that the facial expression representation based on stationary velocity fields can be successfully utilised in facial expression recognition, and this parameterisation produces a higher recognition rate than the facial expression representation based on deformation fields.
|Item Type:||Book Section|
|Uncontrolled Keywords (separate with ;):||Facial expression representation; Facial expression recognition; Vectorial log-Euclidean statistics; Statistical shape modelling; Diffeomorphic image registration; Systems Theory, Control; Optimization; Math Applications in Computer Science; Pattern Recognition|
|Schools:||Faculty of Science and Technology > School of Engineering|
|Deposited By:||Wei Quan|
|Deposited On:||04 Jan 2013 10:26|
|Last Modified:||17 May 2016 12:35|
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