3D Morphable Model Construction for Robust Ear and Face Recognition

Bustard, John and Nixon, Mark (2010) 3D Morphable Model Construction for Robust Ear and Face Recognition. At IEEE Conf. Computer Vision and Patern Recognition CVPR 10, San Francisco, IEEE.


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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.

Item Type: Conference or Workshop Item (Speech)
Additional Information: Event Dates: June 2010
Divisions : Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Southampton Wireless Group
ePrint ID: 270902
Accepted Date and Publication Date:
June 2010Accepted
Date Deposited: 22 Apr 2010 09:26
Last Modified: 31 Mar 2016 14:17
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/270902

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