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In this paper we present a novel method that combines a HK curvature-basedapproach for three-dimensional (3D) face detection in different poses (X-axis,Y-axis and Z-axis). Salient face features, such as the eyes and nose, aredetected through an analysis of the curvature of the entire facial surface. Allthe experiments have been performed on the FRAV3D Database. After applying theproposed algorithm to the 3D facial surface we have obtained considerably goodresults i.e. on 752 3D face images our method detected the eye corners for 543face images, thus giving a 72.20% of eye corners detection and 743 face imagesfor nose-tip detection thus giving a 98.80% of good nose tip localization

A novel approach to nose-tip and eye corners detection using H-K Curvature Analysis in case of 3D images