By the same authors

A Data-augmented 3D Morphable Model of the Ear

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Title of host publicationThe 13th IEEE International Conference on AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2018)
DateAccepted/In press - 25 Jan 2018
DatePublished (current) - 15 May 2018
Number of pages5
PublisherIEEE
Original languageEnglish
ISBN (Print)9781538623350

Abstract

Morphable models are useful shape priors for biometric recognition tasks.
Here we present an iterative process of refinement for a 3D Morphable Model (3DMM) of the human ear that employs data augmentation. The process employs the following stages
1) landmark-based 3DMM fitting; 2) 3D template deformation to overcome noisy over-fitting; 3) 3D mesh editing, to improve the fit to manual 2D landmarks. These processes are wrapped in an iterative procedure that is able to bootstrap a weak, approximate model into a significantly better model. Evaluations using several performance metrics verify the improvement of our model using the proposed algorithm. We use this new 3DMM model-booting algorithm to generate a refined 3D morphable model of the human ear, and we make this new model and our augmented training dataset public.

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© 2018 IEEE. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

    Research areas

  • 3D Morphable Model; 3D shape registration; 3D image analysis

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