A spatiotemporal feature-based approach for facial expression recognition from depth video

Md. Zia Uddin

doi:10.1117/12.2197074

6 July 2015 A spatiotemporal feature-based approach for facial expression recognition from depth video

Md. Zia Uddin

Proceedings Volume 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015); 96311C (2015) https://doi.org/10.1117/12.2197074
Event: Seventh International Conference on Digital Image Processing (ICDIP15), 2015, Los Angeles, United States

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.

Citation Download Citation

Md. Zia Uddin "A spatiotemporal feature-based approach for facial expression recognition from depth video", Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 96311C (6 July 2015); https://doi.org/10.1117/12.2197074

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KEYWORDS

Independent component analysis

Optical flow

Facial recognition systems

Feature extraction

Principal component analysis

Video

Motion models

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