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Carnegie Mellon Robotics Institute

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Abstract

We propose a model- and exemplar-based approach for face recognition. This problem has been previously tackled using either models or exemplars, with limited success. Our idea uses models to synthesize many more exemplars, which are then used in the learning stage of a face recognition system. To demonstrate this, we develop a statistical shape-from-shading model to recover face shape from a single image, and to synthesize the same face under new illumination. We then use this to build a simple and fast classifier that was not possible before because of a lack of training data.

Keywords

model-based, exemplar-based, shape-from-shading, face recognition, eigenspace

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): Face Group and Component Analysis

Associated Project(s): Face Recognition Across Illumination and Face Recognition

Text Reference

Terence Sim and Takeo Kanade, "Combining Models and Exemplars for Face Recognition: An Illuminating Example," Proceedings of the CVPR 2001 Workshop on Models versus Exemplars in Computer Vision, December, 2001.

BibTeX Reference

@inproceedings{Sim_2001_3870,
   author = "Terence Sim and Takeo Kanade",
   title = "Combining Models and Exemplars for Face Recognition: An Illuminating Example",
   booktitle = "Proceedings of the CVPR 2001 Workshop on Models versus Exemplars in Computer Vision",
   month = "December",
   year = "2001",
}

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