An evaluation of multimodal 2D+3D face biometrics

By Kyong I. Chang, Kevin W. Bowyer, Patrick J. Flynn. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005

506 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/5e13cdc9347b92e5757498d79296606300df2d6c

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Citations in the corpus

Multiple Nose Region Matching for 3D Face Recognition under Varying Facial Expression (2006, methodology): “For the baseline algorithms, we use a PCA approach similar to previous work [1], [13], [14] and an iterative closest point (ICP) approach similar to previous work [2], [10], [15].”
A 3D Face Model for Pose and Illumination Invariant Face Recognition (2009, methodology): “As test set we use the UND database [9] that consists of 953 unregistered 3D scans, with one to eight scans per subject.”
Image understanding for iris biometrics: A survey (2008, background): “In biometrics in general, it has been found that using multiple samples for enrollment and comparing the probe to multiple gallery samples will result in improved performance [13,19,120].”
A 3D facial expression database for facial behavior research (2006, unknown): “The lack of an accredited common database (like the FERET and FRGC databases for face recognition) and evaluation methodology makes it difficult to compare, validate, resolve, and extend the issues concerned with 3D facial expression analysis.”
Expression invariant 3D face recognition with a Morphable Model (2008, methodology): “The recognition rates on the GavabDB without expression model are not quite as good as for the expression-less UND dataset, so here we hope to find some improvement by using expression normalization.”
Three-Dimensional Face Recognition in the Presence of Facial Expressions: An Annotated Deformable Model Approach (2007, background): “0162-8828/07/$25.00 2007 IEEE Published by the IEEE Computer Society Bowyer et al. [1] and Chang et al. [ 3 ].”
Human Ear Recognition in 3D (2007, background): “More work on the 3D face biometrics can be found in [14], [15], [16], [17], [18], [19], [20].”
Illumination Invariant Face Recognition Using Near-Infrared Images (2007, background): “More importantly, it is shown that the 3D method may not necessarily produce better recognition results: recognition performances achieved by using a single 2D image and by a single 3D image are similar [32].”