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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bustard, J.D. Nixon, M.S. |
| Copyright Year | 2010 |
| Description | Author affiliation: ISIS, School of Electronics and Computer Science, University of Southampton, Southampton, U.K. (Bustard, J.D.; Nixon, M.S.) |
| Abstract | Recent work suggests that the human ear varies significantly between different subjects and can be used for identification. In principle, therefore, using ears in addition to the face within a recognition system could improve accuracy and robustness, particularly for non-frontal views. The paper describes work that investigates this hypothesis using an approach based on the construction of a 3D morphable model of the head and ear. One issue with creating a model that includes the ear is that existing training datasets contain noise and partial occlusion. Rather than exclude these regions manually, a classifier has been developed which automates this process. When combined with a robust registration algorithm the resulting system enables full head morphable models to be constructed efficiently using less constrained datasets. The algorithm has been evaluated using registration consistency, model coverage and minimalism metrics, which together demonstrate the accuracy of the approach. To make it easier to build on this work, the source code has been made available online. |
| Starting Page | 2582 |
| Ending Page | 2589 |
| File Size | 2116496 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424469840 |
| ISSN | 10636919 |
| e-ISBN | 9781424469857 |
| DOI | 10.1109/CVPR.2010.5539968 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-06-13 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Ear Face recognition Noise robustness Humans Noise shaping Shape Intersymbol interference Surgery Fitting Training data |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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