Type of Publication

Poster

Date:

10 /

2018

Status

Published

Improving Facial Depth Data by Exemplar-based Comparisons

Featured in:

Recpad 2018-24th Portuguese Conference on Pattern Recognition

Authors:

Leandro Dihl, Leandro Cruz and Nuno Gonçalves

Abstract

3D face models are widely used for several purposes, such as biometric systems, face verification, facial expression recognition, 3D visualization, etc. They can be captured by using different types of devices, like plenop- tic cameras, structured light cameras, time of flight, etc. Nevertheless, the model generated by all of these consumers devices are very noisy. In this work, we present a filtering method for meshes of faces preserving their intrinsic features. It is based in an exemplar-based neighborhood matching where all models are in a frontal position avoiding rotation and perspective drawbacks. Moreover, the model is invariant to depth transla- tion and scale. The obtained results showed that this method is robust and promising.

Citation
Leandro Dihl, Leandro Cruz and Nuno Gonçalves (2018, October). Improving Facial Depth Data by Exemplar-based Comparisons In Recpad 2018 (Posters) (pp. 126-128).

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