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.
Keywords
Artificial intelligenceComputer scienceComputer visionFace (sociological concept)Facial recognition systemPattern recognition (psychology)Solid modelingComputer graphicsTexture (cosmology)Range (aeronautics)3d modelImage textureStatistical modelSet (abstract data type)Image (mathematics)Image processing
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Publication Info
- Year
- 2003
- Type
- article
- Volume
- 25
- Issue
- 9
- Pages
- 1063-1074
- Citations
- 1988
- Access
- Closed
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Cite This
Volker Blanz,
Thomas Vetter
(2003).
Face recognition based on fitting a 3D morphable model.
IEEE Transactions on Pattern Analysis and Machine Intelligence
, 25
(9)
, 1063-1074.
https://doi.org/10.1109/tpami.2003.1227983
Identifiers
- DOI
- 10.1109/tpami.2003.1227983