Result Details
3D Face Recognition on Low-Cost Depth Sensors
Drahanský Martin, prof. Ing., Ph.D., RE-OPPaTT (RO), DITS (FIT)
Dvořák Radim, Ing., Ph.D.
Provazník Valentýna, prof. Ing., Ph.D., UBMI (FEEC)
Váňa Jan, Ing., DIFS (FIT)
This paper deals with the biometric recognition of 3D faces with the emphasis on the low-cost depth sensors; such are Microsoft Kinect and SoftKinetic DS325. The presented approach is based on the score-level fusion of individual recognition units. Each unit processes the input face mesh and produces a curvature, depth, or texture representation. This image representation is further processed by specific Gabor or Gauss-Laguerre complex filter. The absolute response is then projected to lower-dimension representations and the feature vector is thus extracted. Comparison scores of individual recognition units are combined using transformation-based, classifier-based, or density-based score-level fusion. The results suggest that even poor quality low-resolution scans containing holes and noise might be successfully used for recognition in relatively small databases.
3D face recognition, score-level fusion, biometrics, Gabor filter, Gauss-Laguerre filter
@inproceedings{BUT111626,
author="Štěpán {Mráček} and Martin {Drahanský} and Radim {Dvořák} and Valentýna {Provazník} and Jan {Váňa}",
title="3D Face Recognition on Low-Cost Depth Sensors",
booktitle="Proceedings of the International Conference of Biometrics Special Interest Group (BIOSIG 2014)",
year="2014",
journal="GI-Edition Lecture Notes in Informatics (LNI)",
volume="2014",
number="230",
pages="195--202",
publisher="GI - Group for computer science",
address="Darmstadt",
isbn="978-3-88579-624-4",
issn="1617-5468",
url="https://www.fit.vut.cz/research/publication/10679/"
}
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