Paper
29 January 2007 Alternative face models for 3D face registration
Albert Ali Salah, Neşe Alyüz, Lale Akarun
Author Affiliations +
Proceedings Volume 6499, Vision Geometry XV; 64990E (2007) https://doi.org/10.1117/12.705860
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States
Abstract
3D has become an important modality for face biometrics. The accuracy of a 3D face recognition system depends on a correct registration that aligns the facial surfaces and makes a comparison possible. The best results obtained so far use a one-to-all registration approach, which means each new facial surface is registered to all faces in the gallery, at a great computational cost. We explore the approach of registering the new facial surface to an average face model (AFM), which automatically establishes correspondence to the pre-registered gallery faces. Going one step further, we propose that using a couple of well-selected AFMs can trade-off computation time with accuracy. Drawing on cognitive justifications, we propose to employ category-specific alternative average face models for registration, which is shown to increase the accuracy of the subsequent recognition. We inspect thin-plate spline (TPS) and iterative closest point (ICP) based registration schemes under realistic assumptions on manual or automatic landmark detection prior to registration. We evaluate several approaches for the coarse initialization of ICP. We propose a new algorithm for constructing an AFM, and show that it works better than a recent approach. Finally, we perform simulations with multiple AFMs that correspond to different clusters in the face shape space and compare these with gender and morphology based groupings. We report our results on the FRGC 3D face database.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Albert Ali Salah, Neşe Alyüz, and Lale Akarun "Alternative face models for 3D face registration", Proc. SPIE 6499, Vision Geometry XV, 64990E (29 January 2007); https://doi.org/10.1117/12.705860
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Cited by 7 scholarly publications.
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KEYWORDS
Atomic force microscopy

3D modeling

Nose

Facial recognition systems

Detection and tracking algorithms

Mouth

Databases

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