Face detection is a crucial preliminary in many applications. Most of 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 (3D) face detection. Salient face features, such as the eyes and nose, are detected through an analysis of the curvature of the surface. 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. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Colombo, A., Cusano, C., Schettini, R. (2006). 3D face detection using curvature analysis. PATTERN RECOGNITION, 39(3), 444-455 [10.1016/j.patcog.2005.09.009].

3D face detection using curvature analysis

COLOMBO, ALESSANDRO;CUSANO, CLAUDIO;SCHETTINI, RAIMONDO
2006

Abstract

Face detection is a crucial preliminary in many applications. Most of 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 (3D) face detection. Salient face features, such as the eyes and nose, are detected through an analysis of the curvature of the surface. 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. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Articolo in rivista - Articolo scientifico
three-dimensional face detection; face curvatures; HK classification; eigenfaces; face localization
English
mar-2006
39
3
444
455
none
Colombo, A., Cusano, C., Schettini, R. (2006). 3D face detection using curvature analysis. PATTERN RECOGNITION, 39(3), 444-455 [10.1016/j.patcog.2005.09.009].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/13938
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