We describe a method for the automatic identification of facial features (eyes, nose, mouth and chin) and the precise localization of their fiducial points (e.g. nose tip, mouth and eye corners) in color images of face foregrounds. The algorithm requires as input 2D color images, representing face foregrounds with homogeneous background; it is scale-independent, it deals with either frontal, rotated (up to 30°) or slightly tilted (up to 10°) faces, and it is robust to different facial expressions, requiring the mouth closed and the eyes opened, and no wearing glasses. The method proceeds with subsequent refinements: first, it identifies the sub images containing each feature, afterwards, it processes the single features separately by a blend of techniques which use both color and shape information. The system has been tested on three databases: the XM2VTS database, the University of Stirling database, and ours, for a total of 1650 images. The obtained results are described quantitatively and discussed.

Fiducial point localization in color images of face foregrounds / P. Campadelli, R. Lanzarotti. - In: IMAGE AND VISION COMPUTING. - ISSN 0262-8856. - 22:11(2004), pp. 863-872.

Fiducial point localization in color images of face foregrounds

P. Campadelli
Primo
;
R. Lanzarotti
Ultimo
2004

Abstract

We describe a method for the automatic identification of facial features (eyes, nose, mouth and chin) and the precise localization of their fiducial points (e.g. nose tip, mouth and eye corners) in color images of face foregrounds. The algorithm requires as input 2D color images, representing face foregrounds with homogeneous background; it is scale-independent, it deals with either frontal, rotated (up to 30°) or slightly tilted (up to 10°) faces, and it is robust to different facial expressions, requiring the mouth closed and the eyes opened, and no wearing glasses. The method proceeds with subsequent refinements: first, it identifies the sub images containing each feature, afterwards, it processes the single features separately by a blend of techniques which use both color and shape information. The system has been tested on three databases: the XM2VTS database, the University of Stirling database, and ours, for a total of 1650 images. The obtained results are described quantitatively and discussed.
Settore INF/01 - Informatica
2004
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/9788
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