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A morphable model for the synthesis of 3D faces

Matthew Turk
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This article is published in International Conference on Computer Graphics and Interactive Techniques.The article was published on 1999-01-01 and is currently open access. It has received 2010 citations till now.

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Book

Computer Vision: Algorithms and Applications

TL;DR: Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images and takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene.
Journal ArticleDOI

Face recognition based on fitting a 3D morphable model

TL;DR: 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, using computer graphics.
Journal ArticleDOI

2006 Special Issue: Modeling attention to salient proto-objects

TL;DR: It is demonstrated that the suggested model can enable a model of object recognition in cortex to expand from recognizing individual objects in isolation to sequentially recognizing all objects in a more complex scene.
Proceedings ArticleDOI

A 3D Face Model for Pose and Illumination Invariant Face Recognition

TL;DR: This paper publishes a generative 3D shape and texture model, the Basel Face Model (BFM), and demonstrates its application to several face recognition task and publishes a set of detailed recognition and reconstruction results on standard databases to allow complete algorithm comparisons.
Proceedings ArticleDOI

Acquiring the reflectance field of a human face

TL;DR: A method to acquire the reflectance field of a human face and use these measurements to render the face under arbitrary changes in lighting and viewpoint and demonstrates the technique with synthetic renderings of a person's face under novel illumination and viewpoints.
References
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Journal ArticleDOI

Face recognition: A literature survey

TL;DR: In this paper, the authors provide an up-to-date critical survey of still-and video-based face recognition research, and provide some insights into the studies of machine recognition of faces.
Book

Computer Vision: Algorithms and Applications

TL;DR: Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images and takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene.
Journal ArticleDOI

Face recognition based on fitting a 3D morphable model

TL;DR: 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, using computer graphics.
Proceedings ArticleDOI

A 3D Face Model for Pose and Illumination Invariant Face Recognition

TL;DR: This paper publishes a generative 3D shape and texture model, the Basel Face Model (BFM), and demonstrates its application to several face recognition task and publishes a set of detailed recognition and reconstruction results on standard databases to allow complete algorithm comparisons.
Proceedings ArticleDOI

Acquiring the reflectance field of a human face

TL;DR: A method to acquire the reflectance field of a human face and use these measurements to render the face under arbitrary changes in lighting and viewpoint and demonstrates the technique with synthetic renderings of a person's face under novel illumination and viewpoints.
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