Publication detail

3D Face Recognition on Low-Cost Depth Sensors

MRÁČEK, Š. DRAHANSKÝ, M. DVOŘÁK, R. PROVAZNÍK, V. VÁŇA, J.

Original Title

3D Face Recognition on Low-Cost Depth Sensors

Type

conference paper

Language

English

Original Abstract

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.

Keywords

3D face recognition, score-level fusion, biometrics, Gabor filter, Gauss-Laguerre filter

Authors

MRÁČEK, Š.; DRAHANSKÝ, M.; DVOŘÁK, R.; PROVAZNÍK, V.; VÁŇA, J.

RIV year

2014

Released

10. 9. 2014

Publisher

GI - Group for computer science

Location

Darmstadt

ISBN

978-3-88579-624-4

Book

Proceedings of the International Conference of Biometrics Special Interest Group (BIOSIG 2014)

ISBN

1617-5468

Periodical

GI-Edition Lecture Notes in Informatics (LNI)

Year of study

2014

Number

230

State

Federal Republic of Germany

Pages from

195

Pages to

202

Pages count

8

URL

https://www.fit.vut.cz/research/publication/10679/

BibTex

@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/"
}