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: 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), Shanghai, China, 22-26 Apr 2013, ISBN 9781467355469 (doi: 10.1109/FG.2013.6553764)

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 Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Pugeault, Dr Nicolas
• Authors: Sheerman-Chase, T., Ong, E.-J., Pugeault, N., and Bowden, R.
• College/School: College of Science and Engineering > School of Computing Science
• ISBN: 9781467355469
• Published Online: 15 July 2013