Facial Expression Recognition on Hexagonal Structure Using LBP-Based Histogram Variances

Springer Berlin Heildelberg New York
Publication Type:
Wang Lin et al. 2011, 'Facial Expression Recognition on Hexagonal Structure Using LBP-Based Histogram Variances', , Springer Berlin Heildelberg New York, USA, , pp. 35-45.
Issue Date:
Full metadata record
Files in This Item:
Filename Description SizeFormat
2010000317OK.pdf646.47 kBAdobe PDF
In our earlier work, we have proposed an HVF (Histogram Variance Face) approach and proved its effectiveness for facial expression recognition. In this paper, we extend the HVF approach and present a novel approach for facial expression. We take into account the human perspective and understanding of facial expressions. For the first time, we propose to use the Local Binary Pattern (LBP) defined on the hexagonal structure to extract local, dynamic facial features from facial expression images. The dynamic LBP features are used to construct a static image, namely Hexagonal Histogram Variance Face (HHVF), for the video representing a facial expression. We show that the HHVFs representing the same facial expression (e.g., surprise, happy and sadness etc.) are similar no matter if the performers and frame rates are different. Therefore, the proposed facial recognition approach can be utilised for the dynamic expression recognition. We have tested our approach on the well-known Cohn-Kanade AU-Coded Facial Expression database. We have found the improved accuracy of HHVF-based classification compared with the HVF-based approach.
Please use this identifier to cite or link to this item: