A Riemannian Analysis of 3D Nose Shapes for Partial Human Biometrics
Abstract
In this paper we explore the use of shapes of noses for performing partial human biometrics. The basic idea is to represent nasal surfaces using indexed collections of iso-curves, and to analyze shapes of noses by comparing their corresponding curves. We extend past work in Riemannian analysis of shapes of closed curves in R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> to obtain a similar Riemannian analysis for nasal surfaces. In particular, we obtain algorithms for computing geodesics, computing statistical means, and stochastic clustering. We demonstrate these ideas in two application contexts : authentication and identification. We evaluate performances on a large database involving 2000 scans from FRGC v2 database, and present a hierarchical organization of nose databases to allow for efficient searches.
Cite
Text
Drira et al. "A Riemannian Analysis of 3D Nose Shapes for Partial Human Biometrics." IEEE/CVF International Conference on Computer Vision, 2009. doi:10.1109/ICCV.2009.5459451Markdown
[Drira et al. "A Riemannian Analysis of 3D Nose Shapes for Partial Human Biometrics." IEEE/CVF International Conference on Computer Vision, 2009.](https://mlanthology.org/iccv/2009/drira2009iccv-riemannian/) doi:10.1109/ICCV.2009.5459451BibTeX
@inproceedings{drira2009iccv-riemannian,
title = {{A Riemannian Analysis of 3D Nose Shapes for Partial Human Biometrics}},
author = {Drira, Hassen and Amor, Boulbaba Ben and Srivastava, Anuj and Daoudi, Mohamed},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {2009},
pages = {2050-2057},
doi = {10.1109/ICCV.2009.5459451},
url = {https://mlanthology.org/iccv/2009/drira2009iccv-riemannian/}
}