Intelligent Quality Assessment of Geometrical Features for 3D Face Recognition - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

Intelligent Quality Assessment of Geometrical Features for 3D Face Recognition

(1) , , ,
1
F. Marcolin
  • Fonction : Auteur
S. Spada
  • Fonction : Auteur
E. Vezzetti
  • Fonction : Auteur

Résumé

This paper proposes a methodology to assess the discriminative capabilities of geometrical descriptors referring to the public Bosphorus 3D facial database as testing dataset. The investigated descriptors include histogram versions of Shape Index and Curvedness, Euclidean and geodesic distances between facial soft-tissue landmarks. The discriminability of these features is evaluated through the analysis of single block of features and their meanings with different techniques. Multilayer perceptron neural network methodology is adopted to evaluate the relevance of the features, examined in different test combinations. Principle component analysis (PCA) is applied for dimensionality reduction.
Fichier non déposé

Dates et versions

hal-03631443 , version 1 (05-04-2022)

Identifiants

Citer

G. Cirrincione, F. Marcolin, S. Spada, E. Vezzetti. Intelligent Quality Assessment of Geometrical Features for 3D Face Recognition. QUANTIFYING AND PROCESSING BIOMEDICAL AND BEHAVIORAL SIGNALS, Jun 2017, Vietri sul Mare, Italy. pp.253-264, ⟨10.1007/978-3-319-95095-2\_24⟩. ⟨hal-03631443⟩

Collections

U-PICARDIE LTI
2 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook Twitter LinkedIn More