3D face recognition on low-cost depth sensors
| dc.contributor.author | Mráček, Štěpán | |
| dc.contributor.author | Drahanský, Martin | |
| dc.contributor.author | Dvořák, Radim | |
| dc.contributor.author | Provazník, Ivo | |
| dc.contributor.author | Váňa, Jan | |
| dc.contributor.editor | Brömme, Arslan | |
| dc.contributor.editor | Busch, Christoph | |
| dc.date.accessioned | 2017-07-26T10:54:16Z | |
| dc.date.available | 2017-07-26T10:54:16Z | |
| dc.date.issued | 2014 | |
| dc.description.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 lowerdimension representations and the feature vector is thus extracted. Comparison scores of individual recognition units are combined using transformation-based, classifierbased, 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. | en |
| dc.identifier.isbn | 978-3-88579-624-4 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | BIOSIG 2014 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-230 | |
| dc.title | 3D face recognition on low-cost depth sensors | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 202 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 195 | |
| gi.conference.date | 10.-12. September 2014 | |
| gi.conference.location | Darmstadt |
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