3D facial image recognition using a nose volume and curvature based eigenface

Authors:
Yeunghak Lee;Ikdong Kim;Jaechang Shim;David Marshall
Affiliations:
Communitcation Research Centre, Cardiff University, Cardiff, Wales, UK;Dept. of Computer Engineering, Andong National University, Kyungpook, Korea;Dept. of Computer Engineering, Andong National University, Kyungpook, Korea;Communitcation Research Centre, Cardiff University, Cardiff, Wales, UK
Venue:
GMP'06 Proceedings of the 4th international conference on Geometric Modeling and Processing
Year:
2006

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Abstract

The depth information in the face represents personal features in detail. In this study, the important personal facial information was presented by the surface curvatures and the features of vertical and horizontal of nose volume extracted from the face. The approach works by the depth of nose, the area of nose and the volume of nose based both on a vertical and horizontal are calculated. And the principal components analysis (PCA), which is calculated using the curvature data, was presented different features for each person. To classify the faces, the cascade architectures of fuzzy neural networks (CAFNNs), which can guarantee a high recognition rate as well as parsimonious knowledge base, are considered. In the experimental results, 3D images demonstrate the effectiveness of the proposed methods.