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Erschienen in:
Real-Time Semantic Segmentation with Label Propagation Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Fast and Precise Face Alignment and 3D Shape Reconstruction from a Single 2D Image

verfasst von : Ruiqi Zhao, Yan Wang, C. Fabian Benitez-Quiroz, Yaojie Liu, Aleix M. Martinez

Erschienen in: Computer Vision – ECCV 2016 Workshops

Verlag: Springer International Publishing

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Abstract

Many face recognition applications require a precise 3D reconstruction of the shape of the face, even when only a single 2D image is available. We present a novel regression approach that learns to detect facial landmark points and estimate their 3D shape rapidly and accurately from a single face image. The main idea is to regress a function f(.) that maps 2D images of faces to their corresponding 3D shape from a large number of sample face images under varying pose, illumination, identity and expression. To model the non-linearity of this function, we use a deep neural network and demonstrate how it can be efficiently trained using a large number of samples. During testing, our algorithm runs at more than 30 frames/s on an i7 desktop. This algorithm was the top 2 performer in the 3DFAW Challenge.

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Vorheriges Kapitel 3D Face Alignment in the Wild: A Landmark-Free, Nose-Based Approach
Nächstes Kapitel Shape Augmented Regression for 3D Face Alignment
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Metadaten
Titel
Fast and Precise Face Alignment and 3D Shape Reconstruction from a Single 2D Image
verfasst von
Ruiqi Zhao
Yan Wang
C. Fabian Benitez-Quiroz
Yaojie Liu
Aleix M. Martinez
Copyright-Jahr
2016
Buch
Computer Vision – ECCV 2016 Workshops

Print ISBN: 978-3-319-48880-6

Electronic ISBN: 978-3-319-48881-3

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-48881-3_41

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