Face Recognition Based on Fitting a 3D Morphable Model

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Face Recognition Based on Fitting a 3D Morphable Model (2003)

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by Volker Blanz , Thomas Vetter

Venue:	IEEE TRANS. PATTERN ANAL. MACH. INTELL
Citations:	551 - 19 self

BibTeX

@ARTICLE{Blanz03facerecognition,
    author = {Volker Blanz and Thomas Vetter},
    title = {Face Recognition Based on Fitting a 3D Morphable Model},
    journal = {IEEE TRANS. PATTERN ANAL. MACH. INTELL},
    year = {2003},
    volume = {25},
    number = {9},
    pages = {1063--1074}
}

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Abstract

This paper presents a method for face recognition across variations in pose, ranging from frontal to profile views, and across a wide range of illuminations, including cast shadows and specular reflections. To account for these variations, the algorithm simulates the process of image formation in 3D space, using computer graphics, and it estimates 3D shape and texture of faces from single images. The estimate is achieved by fitting a statistical, morphable model of 3D faces to images. The model is learned from a set of textured 3D scans of heads. We describe the construction of the morphable model, an algorithm to fit the model to images, and a framework for face identification. In this framework, faces are represented by model parameters for 3D shape and texture. We present results obtained with 4,488 images from the publicly available CMU-PIE database and 1,940 images from the FERET database.

Keyphrases

morphable model face recognition specular reflection cast shadow available cmu-pie database index term face recognition illumination invariance image formation wide range feret database pose invariance face identification single image deformable model shape estimation computer graphic model parameter present result

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