Paper Info
Title
Local descriptors matching for 3D face recognition
Abstract
An original solution to 3D face recognition, which supports face matching also in the case of probes with varying expressions and missing parts is proposed in this work. Distinguishing traits of the face are captured by first extracting 3D keypoints of the face scan, then measuring how the face surface changes in the neighborhood of the keypoints using a local descriptor. To this end, an adaptation of the meshDOG detector 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 on the Bosphorus database, showing competitive results with respect to existing solutions for 3D face biometrics.
Year
DOI
Venue
2013
10.1109/ICIP.2013.6738765
Image Processing
Keywords
Field
DocType
face recognition,feature extraction,geometry,image matching,3D face biometrics,3D face recognition,3D keypoint extraction,Bosphorus database,face matching,face scan,inlier pairs,local descriptors matching,local keypoint descriptors,matching keypoints,meshDOG detector,multiring geometric histogram descriptor,3D face recognition,3D keypoints
Face matching,Histogram,Computer vision,Facial recognition system,Three-dimensional face recognition,Pattern recognition,Expression (mathematics),Computer science,Feature extraction,Artificial intelligence,Biometrics,Detector
Conference
ISSN
Citations 
PageRank 
1522-4880
2
0.37
References 
Authors
16
4
Name
Order
Citations
PageRank
Naoufel Werghi132641.99
Stefano Berretti288052.33
Alberto Del Bimbo33777420.44
Pietro Pala4123991.64