Low Resolution Sparse Binary Face Patterns

Swathikiran Sudhakaran, Alex Pappachen James

2016

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.

Paper Citation

in Harvard Style

Sudhakaran S. and James A. (2016). Low Resolution Sparse Binary Face Patterns . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 186-191. DOI: 10.5220/0005782601860191

in Bibtex Style

@conference{visapp16,
author={Swathikiran Sudhakaran and Alex Pappachen James},
title={Low Resolution Sparse Binary Face Patterns},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={186-191},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005782601860191},
isbn={978-989-758-175-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - Low Resolution Sparse Binary Face Patterns
SN - 978-989-758-175-5
AU - Sudhakaran S.
AU - James A.
PY - 2016
SP - 186
EP - 191
DO - 10.5220/0005782601860191