Abstract book (pdf) - ICPR 2010

09:00-11:10, Paper TuAT9.9
Robust Regression for Face Recognition
Naseem, Imran, The Univ. of Western Australia
Togneri, Roberto, The Univ. of Western Australia
Bennamoun, Mohammed, The Univ. of Western Australia
In this paper we address the problem of illumination invariant face recognition. Using a fundamental concept that in
general, patterns from a single object class lie on a linear subspace [2], we develop a linear model representing a probe
image as a linear combination of class-specific galleries. In the presence of noise, the well-conditioned inverse problem
is solved using the robust Huber estimation and the decision is ruled in favor of the class with the minimum reconstruction
error. The proposed Robust Linear Regression Classification (RLRC) algorithm is extensively evaluated for two standard
databases and has shown good performance index compared to the state-of-art robust approaches.
09:00-11:10, Paper TuAT9.10
Recognition of Blurred Faces via Facial Deblurring Combined with Blur-Tolerant Descriptors
Hadid, Abdenour, Univ. of Oulu
Nishiyama, Masashi, Toshiba Corp.
Sato, Yoichi, Univ. of Tokyo
Blur is often present in real-world images and significantly affects the performance of face recognition systems. To improve
the recognition of blurred faces, we propose a new approach which inherits the advantages of two recent methods. The
idea consists of first reducing the amount of blur in the images via deblurring and then extracting blur-tolerant descriptors
for recognition. We assess our analysis on real blurred face images (FRGC 1.0 database) and also on face images artificially
degraded by focus blur (FERET database), demonstrating significant performance enhancement compared to the state-ofthe-art.
09:00-11:10, Paper TuAT9.11
Diffusion-Based Face Selective Smoothing in DCT Domain to Illumination Invariant Face Recognition
Ezoji, Mehdi, Amirkabir Univ. of Tech.
Faez, Karim, Amirkabir Univ. of Tech.
In this paper, a diffusion-based iterative algorithm is proposed for illumination invariant face representation using image
selective smoothing in DCT domain. In fact, we split the image I into three parts (R+w)+L of an illumination invariant
component, an oscillating component and a smooth component. At each iteration, the influence of different frequency
sub-bands of image is determined and the additive oscillating component is reduced. The experimental results confirmed
that our approach provides a suitable representation for overcoming illumination variations.
09:00-11:10, Paper TuAT9.12
BioHashing for Securing Fingerprint Minutiae Templates
Belguechi, Rima, National School of Computer Science
Rosenberger, Christophe, Lab. GREYC
Ait Aoudia, Samy, National School of Computer Science
The storage of fingerprints is an important issue as this biometric modality is more and more deployed for real applications.
The a prori impossibility to revoke a biometric template (like a password) in case of theft, is a major concern for privacy
reasons. We propose in this paper a new method to secure fingerprint minutiae templates by storing a bio code while keeping
good recognition results. We show the efficiency of the method in comparison to some published methods for different
scenarios.
09:00-11:10, Paper TuAT9.13
Fusion of an Isometric Deformation Modeling Approach using Spectral Decomposition and a Region-Based Approach
using ICP for Expression-Invariant 3D Face Recognition
Smeets, Dirk, K.U.Leuven
Fabry, Thomas, K.U.Leuven
Hermans, Jeroen, K.U.Leuven
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