Face recognition in the presence of age differences using holistic and subpattern-based approaches

Authors:
Hüseyin Sertbay;Ösen Toygar
Affiliations:
Computer Engineering Department, Eastern Mediterranean University, Mersin, Turkey;Computer Engineering Department, Eastern Mediterranean University, Mersin, Turkey
Venue:
WAV'09 Proceedings of the 3rd WSEAS international symposium on Wavelets theory and applications in applied mathematics, signal processing & modern science
Year:
2009

Citing 9
Cited 1

Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Imprecisely Localized, Partially Occluded, and Expression Variant Faces from a Single Sample per Class

IEEE Transactions on Pattern Analysis and Machine Intelligence
Effective Representation Using ICA for Face Recognition Robust to Local Distortion and Partial Occlusion

IEEE Transactions on Pattern Analysis and Machine Intelligence
MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Random Sampling for Subspace Face Recognition

International Journal of Computer Vision
A study on three linear discriminant analysis based methods in small sample size problem

Pattern Recognition
Eigenfaces for recognition

Journal of Cognitive Neuroscience
A highly scalable incremental facial feature extraction method

Neurocomputing
Computational methods for modeling facial aging: A survey

Journal of Visual Languages and Computing

Face recognition as an airport and seaport security tool

WSEAS Transactions on Information Science and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

The effect of aging on face recognition using holistic and subpattern-based approaches is studied in this paper. The performance analysis of holistic and subpattern-based methods is presented on face recognition in the presence of age progression with specific preprocessing techniques. Original PCA, subspace LDA and subpattern-based counterparts of these holistic methods are used as feature extractors with the combination of the preprocessing techniques of histogram equalization and mean-and-variance normalization in order to nullify the effect of illumination changes which are known to significantly degrade recognition performance. The recognition performance of the holistic approaches is compared with the performance of subpattern-based PCA and subpattern-based subspace LDA approaches in order to demonstrate the performance differences and similarities between these two types of approaches. To be consistent with the research of others, our work has been tested on two publicly available databases namely FGNET and MORPH. The experiments are performed on these aging databases to demonstrate the recognition performances of the holistic and subpattern-based approaches in the presence of age differences on the faces.