3D face detection using curvature analysis

Face detection is a crucial preliminary in many applications. Most all the approaches to face detection have focused on the use of two-dimensional images. We present an innovative method that combines a feature-based approach with a holistic one for three-dimensional face detection. Salient face features, such as the eyes and nose, are detected through an analysis of the curvature of the surface. In a second stage, each triplet consisting of a candidate nose and two candidate eyes is processed by a PCA-based classifier trained to discriminate between faces and non-faces. The method has been tested, with good results, on some 150 3D faces acquired by a laser range scanner.

• Type: Journal
• Year: 2006
• Where: PR
• Authors: Alessandro Colombo, Claudio Cusano, Raimondo Schettini
• Keywords: Face Detection, Feature-based Approach, PR 2006, Three-dimensional Face Detection