Methods for face detection and adaptive face recognition

Pavani, Sri-Kaushik

Methods for face detection and adaptive face recognition

Document Type

Doctoral thesis
Published Version

Author

Pavani, Sri-Kaushik

Director

Delgado Gómez, David
Frangi Caregnato, Alejandro

Publication Date

2010-07-21

Citation

Pavani, S. Methods for face detection and adaptive face recognition. Universitat Pompeu Fabra; 2010. handle: http://hdl.handle.net/10803/7567

This citation was generated automatically.

Doctoral program

Programa de doctorat en Tecnologies de la Informació i les Comunicacions

Abstract

The focus of this thesis is on facial biometrics; specifically in the problems of face detection and face recognition. Despite intensive research over the last 20 years, the technology is not foolproof, which is why we do not see use of face recognition systems in critical sectors such as banking. In this thesis, we focus on three sub-problems in these two areas of research. Firstly, we propose methods to improve the speed-accuracy trade-off of the state-of-the-art face detector. Secondly, we consider a problem that is often ignored in the literature: to decrease the training time of the detectors. We propose two techniques to this end. Thirdly, we present a detailed large-scale study on self-updating face recognition systems in an attempt to answer if continuously changing facial appearance can be learnt automatically.
L'objectiu d'aquesta tesi és sobre biometria facial, específicament en els problemes de detecció de rostres i reconeixement facial. Malgrat la intensa recerca durant els últims 20 anys, la tecnologia no és infalible, de manera que no veiem l'ús dels sistemes de reconeixement de rostres en sectors crítics com la banca. En aquesta tesi, ens centrem en tres sub-problemes en aquestes dues àrees de recerca. En primer lloc, es proposa mètodes per millorar l'equilibri entre la precisió i la velocitat del detector de cares d'última generació. En segon lloc, considerem un problema que sovint s'ignora en la literatura: disminuir el temps de formació dels detectors. Es proposen dues tècniques per a aquest fi. En tercer lloc, es presenta un estudi detallat a gran escala sobre l'auto-actualització dels sistemes de reconeixement facial en un intent de respondre si el canvi constant de l'aparença facial es pot aprendre de forma automàtica.

Keywords

Fisher's LDA, Gaussian weak classifiers, Weak classifier, Variance normalization, Transductive reasoning, training complexity, rejection cascade, fusion of p-values, OSTCM-kNN classifier, integrated Performance Primitives, impostor detection, haar-like features, fusion of shape and texture, face recognition system, delaunay triangulation, MIT+CMU face database, YT database, GEFA database, temporal confidence, segmentation confidence, face detector confidence, classification confidence, laplacian clutter model, clutter models, changes in facial appearance, face segmentation, face normalization, face detection, automatic face recognition system