Weight-Based Facial Expression Recognition from Near-Infrared Video Sequences

Authors:
Matti Taini;Guoying Zhao;Matti Pietikäinen
Affiliations:
Machine Vision Group, Infotech Oulu and Department of Electrical and Information Engineering, University of Oulu, Finland FI-90014;Machine Vision Group, Infotech Oulu and Department of Electrical and Information Engineering, University of Oulu, Finland FI-90014;Machine Vision Group, Infotech Oulu and Department of Electrical and Information Engineering, University of Oulu, Finland FI-90014
Venue:
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Year:
2009

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Weight-Based Facial Expression Recognition from Near-Infrared Video Sequences

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Weight-Based Facial Expression Recognition from Near-Infrared Video Sequences

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Abstract

This paper presents a novel weight-based approach to recognize facial expressions from the near-infrared (NIR) video sequences. Facial expressions can be thought of as specific dynamic textures where local appearance and motion information need to be considered. The face image is divided into several regions from which local binary patterns from three orthogonal planes (LBP-TOP) features are extracted to be used as a facial feature descriptor. The use of LBP-TOP features enables us to set different weights for each of the three planes (appearance, horizontal motion and vertical motion) inside the block volume. The performance of the proposed method is tested in the novel NIR facial expression database. Assigning different weights to the planes according to their contribution improves the performance. NIR images are shown to deal with illumination variations comparing with visible light images.