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3D Face Recognition using Cumulative Histogram of Surface Curvature  

이영학 (영남대학교 전자정보공학부)
배기억 (영남대학교 전자정보공학)
이태흥 (영남대학교 전자정보공학부)
Publication Information
Journal of KIISE:Software and Applications / v.31, no.5, 2004 , pp. 605-616 More about this Journal
Abstract
A new practical implementation of a facial verification system using cumulative histogram of surface curvatures for the local and contour line areas is proposed, in this paper. The approach works by finding the nose tip that has a protrusion shape on the face. In feature recognition of 3D face images, one has to take into consideration the orientated frontal posture to normalize after extracting face area from the original image. The feature vectors are extracted by using the cumulative histogram which is calculated from the curvature of surface for the contour line areas: 20, 30 and 40, and nose, mouth and eyes regions, which has depth and surface characteristic information. The L1 measure for comparing two feature vectors were used, because it was simple and robust. In the experimental results, the maximum curvature achieved recognition rate of 96% among the proposed methods.
Keywords
3D face recognition; curvature; histogram;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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