A Riemannian analysis of 3D nose shapes for partial human biometrics

Hassen Drira (1, 2) , Ben Amor Boulbaba (2, 1) , Srivastava Anuj (3) , Daoudi Mohamed (2, 1)

1 Institut TELECOM/TELECOM Lille1
2 LIFL - FOX MIIRE
3 Department of Statistics [Tallahassee, FL]

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 isocurves, and to analyze shapes of noses by comparing their corresponding curves. We extend past work in Riemannian analysis of shapes of closed curves in R3 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.

Mots clés: Partial biometrics; riemannian geometry

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Hassen Drira, Ben Amor Boulbaba, Srivastava Anuj, Daoudi Mohamed. A Riemannian analysis of 3D nose shapes for partial human biometrics. International Conference on Computer Vision, Sep 2009, Japan. pp.2050-2057. ⟨hal-00667580⟩