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Cited by 442

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An evaluation of multimodal 2D+3D face biometrics

Chang, K.I., Bowyer, K.W., Flynn, P.J.·2005·IEEE Transactions on Pattern Analysis and Machine Intelligence

Abstract

We report on the largest experimental study to date in multimodal 2D+3D face recognition, involving 198 persons in the gallery and either 198 or 670 time-lapse probe images. PCA-based methods are used separately for each modality and match scores in the separate face spaces are combined for multimodal recognition. Major conclusions are: 1) 2D and 3D have similar recognition performance when considered individually, 2) combining 2D and 3D results using a simple weighting scheme outperforms either 2D or 3D alone, 3) combining results from two or more 2D images using a similar weighting scheme also outperforms a single 2D image, and 4) combined 2D+3D outperforms the multiimage 2D result. This is the first (so far, only) work to present such an experimental control to substantiate multimodal performance improvement.

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Metadata

Authors
Chang, K. I., Bowyer, K. W., & Flynn, P. J.
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Published
2005-04
Volume
27
Issue
4
Pages
619-624
ISSN
  • 0162-8828 (ISSN-L)
  • 2160-9292
OpenAlex
W2143542740
Cited by
442
References
0
FWCI
61.83
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: An evaluation of multimodal 2D+3D face biometrics. https://app.cochat.ai/papers/10.1109/tpami.2005.70
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Chang, K. I., Bowyer, K. W., & Flynn, P. J. (2005). An evaluation of multimodal 2D+3D face biometrics. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2005.70

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