Selecting of 3D geometric features by boosting for face recognition

被引：1

作者：

Ballihi, Lahoucine ^{[1
,2
]}

Ben Amor, Boulbaba ^{[1
,3
]}

Daoudi, Mohamed ^{[1
,3
]}

Srivastava, Anuj ^{[4
]}

Aboutajdine, Driss ^{[2
]}

机构：

[1] Univ Lille 1, LIFL UMR USTL CNRS 8022, F-59650 Villeneuve Dascq, France

[2] Univ Mohammed 5, LRIT, Unite Assoc CNRST URAC 29, Rabat, Morocco

[3] Inst Mines Telecom, Villeneuve Dascq, France

[4] Florida State Univ, Dept Stat, Tallahassee, FL 32306 USA

来源：

TRAITEMENT DU SIGNAL | 2012年 / 29卷 / 3-5期

关键词：

geometric features; riemannian geometry; geodesic path; facial curves; AdaBoost;

D O I：

10.3166/TS.29.383-407

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The proposed framework combines machine learning techniques and Riemannian geometry-based shape analysis. We represent facial surfaces by collections of radial curves and iso-level curves, the shapes of corresponding curves are compared using a Riemmannian framework We select the most discriminative curves using the well known AdaBoost algorithm. The experiment involving FRGC v2 dataset demonstrates the effectiveness of this feature selection by achieving 98.02 % as rank-1 recognition rate.

引用

页码：383 / 407

页数：25

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