Face Recognition Based on Fitting a 3D Morphable Model

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

by Volker Blanz , Thomas Vetter

Venue:	IEEE Trans. Pattern Anal. Mach. Intell
Citations:	251 - 11 self

Datum	Value	Source
TITLE	Face Recognition Based on Fitting a 3D Morphable Model	SVM HeaderParse 0.2
AUTHOR NAME	Volker Blanz	SVM HeaderParse 0.2
AUTHOR NAME	Thomas Vetter	SVM HeaderParse 0.2
ABSTRACT	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. Index Terms—Face recognition, shape estimation, deformable model, 3D faces, pose invariance, illumination invariance. æ 1	SVM HeaderParse 0.2
YEAR	2003	INFERENCE
VENUE	IEEE Trans. Pattern Anal. Mach. Intell	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	1063--1074	INFERENCE
CITATIONS	39 found	ParsCit 1.0