Authors:
Swathikiran Sudhakaran
1
and
Alex Pappachen James
2
Affiliations:
1
Fondazione Bruno Kessler, Italy
;
2
Nazarbayev University, Kazakhstan
Keyword(s):
Low Resolution, Face Recognition, Thumbnails, Wavelet Transform, Local Binary Pattern, Nearest Neighbour, Sparse Coding.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Early and Biologically-Inspired Vision
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
Abstract:
Automated recognition of low resolution face images from thumbnails represent a challenging image recognition problem. We propose the sequential fusion of wavelet transform computation, local binary pattern and sparse coding of images to accurately extract facial features from thumbnail images. A minimum distance classifier with Shepard's similarity measure is used as the classifier. The proposed method shows robust recognition performance when tested on face datasets (Yale B, AR and PUT) when compared against benchmark techniques for very low resolution (i.e. less than 45x45 pixels) face image recognition. The possible applications of the proposed thumbnail recognition include contextual search, intelligent image/video sorting and groups, and face image clustering.