A 3D Face Recognition Algorithm Using Histogram-based Features

We present an automatic face recognition approach, which relies on the analysis of the three-dimensional facial surface. The proposed approach consists of two basic steps, namely a precise fully automatic normalization stage followed by a histogram-based feature extraction algorithm. During normalization the tip and the root of the nose are detected and the symmetry axis of the face is determined using a PCA analysis and curvature calculations. Subsequently, the face is realigned in a coordinate system derived from the nose tip and the symmetry axis, resulting in a normalized 3D model. The actual region of the face to be analyzed is determined using a simple statistical method. This area is split into disjoint horizontal subareas and the distribution of depth values in each subarea is exploited to characterize the face surface of an individual. Our analysis of the depth value distribution is based on a straightforward histogram analysis of each subarea. When comparing the feature vect...

• Type: Conference
• Year: 2008
• Where: 3DOR
• Authors: Xuebing Zhou, Helmut Seibert, Christoph Busch, Wolfgang Funk
• Keywords: 3DOR 2008, Computer Graphics, Face Recognition Approach, Histogram Analysis, Symmetry Axis