Improving Recognition and Identification of Facial Areas Involved in Non-verbal Communication by Feature Selection

Sheerman-Chase, T, Ong, E-J, Pugeault, N and Bowden, R (2013) Improving Recognition and Identification of Facial Areas Involved in Non-verbal Communication by Feature Selection In: 10th IEEE Conference on Automatic Face and Gesture Recognition (FG), 2013-04-22 - 2013-04-26, Shanghai, China.

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Abstract

Meaningful Non-Verbal Communication (NVC) signals can be recognised by facial deformations based on video tracking. However, the geometric features previously used contain a significant amount of redundant or irrelevant information. A feature selection method is described for selecting a subset of features that improves performance and allows for the identification and visualisation of facial areas involved in NVC. The feature selection is based on a sequential backward elimination of features to find a effective subset of components. This results in a significant improvement in recognition performance, as well as providing evidence that brow lowering is involved in questioning sentences. The improvement in performance is a step towards a more practical automatic system and the facial areas identified provide some insight into human behaviour.

Item Type:	Conference or Workshop Item (Conference Paper)
Divisions :	Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :	Name Email ORCID Sheerman-Chase, T Ong, E-J Pugeault, N Bowden, R
Date :	22 April 2013
DOI :	10.1109/FG.2013.6553764
Depositing User :	Symplectic Elements
Date Deposited :	13 Dec 2013 13:46
Last Modified :	31 Oct 2017 15:11
URI:	http://epubs.surrey.ac.uk/id/eprint/797496

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