Geometric Histograms of 3D Keypoints for Face Identification with Missing Parts

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Date
2013
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
In this work, an original solution to 3D face identification is proposed, which supports recognition also in the case of probes with missing parts. Distinguishing traits of the face are captured by first extracting 3D keypoints of a face scan, then measuring how the face surface changes in the keypoints neighborhood using a local descriptor. To this end, an adaptation of the meshDOG algorithm to the case of 3D faces is proposed, together with a multi-ring geometric histogram descriptor. Face similarity is then evaluated by comparing local keypoint descriptors across inlier pairs of matching keypoints between probe and gallery scans. Experiments have been performed to assess the keypoints distribution and repeatability. Recognition accuracy of the proposed approach has been evaluated on the Bosphorus database, showing competitive results with respect to existing 3D face biometrics solutions.
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@inproceedings{
10.2312:3DOR/3DOR13/057-064
, booktitle = {
Eurographics Workshop on 3D Object Retrieval
}, editor = {
Umberto Castellani and Tobias Schreck and Silvia Biasotti and Ioannis Pratikakis and Afzal Godil and Remco Veltkamp
}, title = {{
Geometric Histograms of 3D Keypoints for Face Identification with Missing Parts
}}, author = {
Berretti, Stefano
and
Werghi, Naoufel
and
Bimbo, Alberto del
and
Pala, Pietro
}, year = {
2013
}, publisher = {
The Eurographics Association
}, ISSN = {
1997-0463
}, ISBN = {
978-3-905674-44-6
}, DOI = {
10.2312/3DOR/3DOR13/057-064
} }
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