Name
Abstract | ||
|---|---|---|
In this work, we propose and experiment an original solution to 3D face recognition that supports accurate face matching also in cases where just some parts of probe scans are available. In the proposed approach, distinguishing traits of the face are captured by first extracting keypoints of the 3D depth image and then measuring how the face depth changes in the keypoints neighborhood using local shape descriptors. Face similarity is evaluated by comparing local shape descriptors across inlier pairs of keypoints that match between probe and gallery scans. The recognition accuracy of the approach is experimented using the Face Recognition Grand Challenge v2.0 data set. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2072572.2072591 | J-HGBU@MM |
Keywords | Field | DocType |
probe scan,face similarity,accurate face,recognition accuracy,face recognition,keypoints neighborhood,face depth change,partial face,depth image,local shape descriptors,face recognition grand challenge | Face matching,Computer vision,Facial recognition system,Three-dimensional face recognition,Pattern recognition,Face Recognition Grand Challenge,Artificial intelligence,Mathematics | Conference |
Citations | PageRank | References |
4 | 0.39 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefano Berretti | 1 | 880 | 52.33 |
| Alberto Del Bimbo | 2 | 3777 | 420.44 |
| Pietro Pala | 3 | 1239 | 91.64 |