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Proceedings Paper

A spatiotemporal feature-based approach for facial expression recognition from depth video
Author(s): Md. Zia Uddin
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Paper Abstract

In this paper, a novel spatiotemporal feature-based method is proposed to recognize facial expressions from depth video. Independent Component Analysis (ICA) spatial features of the depth faces of facial expressions are first augmented with the optical flow motion features. Then, the augmented features are enhanced by Fisher Linear Discriminant Analysis (FLDA) to make them robust. The features are then combined with on Hidden Markov Models (HMMs) to model different facial expressions that are later used to recognize appropriate expression from a test expression depth video. The experimental results show superior performance of the proposed approach over the conventional methods.

Paper Details

Date Published: 6 July 2015
PDF: 5 pages
Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 96311C (6 July 2015); doi: 10.1117/12.2197074
Show Author Affiliations
Md. Zia Uddin, Sungkyunkwan Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 9631:
Seventh International Conference on Digital Image Processing (ICDIP 2015)
Charles M. Falco; Xudong Jiang, Editor(s)

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