Publication Details
3D Face Recognition on Low-Cost Depth Sensors
Drahanský Martin, prof. Ing., Ph.D.
Dvořák Radim, Ing., Ph.D.
Provazník Valentine, prof. Ing., Ph.D. (UBMI)
Váňa Jan, Ing.
3D face recognition, score-level fusion, biometrics, Gabor filter, Gauss-Laguerre filter
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.
@inproceedings{BUT111626,
author="Štěpán {Mráček} and Martin {Drahanský} and Radim {Dvořák} and Valentine {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/"
}