Abstract
| Original language | Undefined |
|---|---|
| Title of host publication | 5th IAPR International Conference on Biometrics, ICB 2012 |
| Place of Publication | USA |
| Publisher | IEEE Computer Society |
| Pages | 111-118 |
| Number of pages | 8 |
| ISBN (Print) | 978-1-4673-0396-5 |
| DOIs | |
| Publication status | Published - 1 Apr 2012 |
| Event | 5th IAPR International Conference on Biometrics, ICB 2012 - ITC Sheraton, New Delhi, India Duration: 29 Mar 2012 → 1 Apr 2012 http://icb12.iiitd.ac.in/ |
Publication series
| Name | |
|---|---|
| Publisher | IEEE Computer Society |
Conference
| Conference | 5th IAPR International Conference on Biometrics, ICB 2012 |
|---|---|
| Abbreviated title | ICB |
| Country | India |
| City | New Delhi |
| Period | 29/03/12 → 1/04/12 |
| Internet address |
Keywords
- METIS-287860
- Biometrics
- IR-81247
- Pattern Recognition
- EWI-21548
- Computer Vision
- SCS-Safety
- CR-I.5
- Face Recognition
Cite this
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Robust 3D Face Recognition in the Presence of Realistic Occlusions. / Alyuz, Nese; Gökberk, B.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Akarun, Lale.
5th IAPR International Conference on Biometrics, ICB 2012. USA : IEEE Computer Society, 2012. p. 111-118.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Robust 3D Face Recognition in the Presence of Realistic Occlusions
AU - Alyuz, Nese
AU - Gökberk, B.
AU - Spreeuwers, Lieuwe Jan
AU - Veldhuis, Raymond N.J.
AU - Akarun, Lale
N1 - 10.1109/ICB.2012.6199767
PY - 2012/4/1
Y1 - 2012/4/1
N2 - Facial occlusions pose significant problems for automatic face recognition systems. In this work, we propose a novel occlusion-resistant three-dimensional (3D) facial identification system. We show that, under extreme occlusions due to hair, hands, and eyeglasses, typical 3D face recognition systems exhibit poor performance. In order to deal with occlusions, our proposed system employs occlusion-resistant registration, occlusion detection, and regional classifiers. A two-step registration module first detects the nose region on the curvedness-weighted convex shape index map, and then performs fine alignment using nose-based Iterative Closest Point (ICP) algorithm. Occluded areas are determined automatically via a generic face model. After non-facial parts introduced by occlusions are removed, a variant of Gappy Principal Component Analysis (Gappy PCA) is used to restore the full face from occlusion-free facial surfaces. Experimental results obtained on realistically occluded facial images from the Bosphorus 3D face database shows that, with the use of score-level fusion of regional Linear Discriminant Analysis (LDA) classifiers, the proposed method improves rank-1 identification accuracy significantly: from 76.12% to 94.23%.
AB - Facial occlusions pose significant problems for automatic face recognition systems. In this work, we propose a novel occlusion-resistant three-dimensional (3D) facial identification system. We show that, under extreme occlusions due to hair, hands, and eyeglasses, typical 3D face recognition systems exhibit poor performance. In order to deal with occlusions, our proposed system employs occlusion-resistant registration, occlusion detection, and regional classifiers. A two-step registration module first detects the nose region on the curvedness-weighted convex shape index map, and then performs fine alignment using nose-based Iterative Closest Point (ICP) algorithm. Occluded areas are determined automatically via a generic face model. After non-facial parts introduced by occlusions are removed, a variant of Gappy Principal Component Analysis (Gappy PCA) is used to restore the full face from occlusion-free facial surfaces. Experimental results obtained on realistically occluded facial images from the Bosphorus 3D face database shows that, with the use of score-level fusion of regional Linear Discriminant Analysis (LDA) classifiers, the proposed method improves rank-1 identification accuracy significantly: from 76.12% to 94.23%.
KW - METIS-287860
KW - Biometrics
KW - IR-81247
KW - Pattern Recognition
KW - EWI-21548
KW - Computer Vision
KW - SCS-Safety
KW - CR-I.5
KW - Face Recognition
U2 - 10.1109/ICB.2012.6199767
DO - 10.1109/ICB.2012.6199767
M3 - Conference contribution
SN - 978-1-4673-0396-5
SP - 111
EP - 118
BT - 5th IAPR International Conference on Biometrics, ICB 2012
PB - IEEE Computer Society
CY - USA
ER -