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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.

Record type: Conference or Workshop Item (Other)

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.

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More information

Accepted/In Press date: June 2010
Additional Information: Event Dates: June 2010
Venue - Dates: IEEE Conf. Computer Vision and Patern Recognition CVPR 10, 2010-06-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 270902
URI: http://eprints.soton.ac.uk/id/eprint/270902
PURE UUID: 1e3a982f-efec-43a0-b445-4d7525efbf39

Catalogue record

Date deposited: 22 Apr 2010 09:26
Last modified: 18 Jul 2017 06:50

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Contributors

Author: John Bustard
Author: Mark Nixon

University divisions

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