Eyeglasses detection on face images using PCA

Detecting the presence of eyeglasses on face images using PCA
533 Downloads
Aktualisiert 6. Apr 2020

Lizenz anzeigen

Download the dataset from the link below, and place the following files in the root:
1- eyeGlasses-faces.mat
2- non-eyeglasses-faces.mat
Each mat file contains 1294 (227x227 pixels) images picked randomly from SoF and FERET datasets. We have used 1294 images for training and 389 images for testing. That is for each class.
To start:
-Run demo.m.
For more information, read report.pdf.
Dataset (cropped images from FEET and Sof datasets):
https://www.dropbox.com/s/ho3ev5e8a4khr0h/dataset.zip?dl=0
SoF dataset:
https://sites.google.com/view/sof-dataset
FERET dataset:
http://www.itl.nist.gov/iad/humanid/feret/feret_master.html

To test using new test images, please edit 'load_data' file accordingly.

Citation:
-----------

If you use this code, please cite the following paper:
Mahmoud Afifi and Mostafa Korashy. "Eyeglasses shop: Eyeglasses replacement system using frontal face image." Proc. 4th Int'l Conf. Mathematics and Information Science (ICMIS). 2015.

BibTeX
----------
@inproceedings{afifi2015eyeglasses,
title={Eyeglasses shop: Eyeglasses replacement system using frontal face image},
author={Afifi, Mahmoud and Korashy, Mostafa},
booktitle={Proc. 4th Int'l Conf. Mathematics and Information Science (ICMIS)},
year={2015}
}

If you use the training dataset in your work, please cite:

1- Mahmoud Afifi, Abdelrahman Abdelhamed. AFIF4: Deep Gender Classification based on AdaBoost-based Fusion of Isolated. Facial Features and Foggy Faces. Journal of Visual Communication and Image representation, 62, 77-86, 2019.
2- P. J. Phillips, P. J. Rauss, and S. Z. Der, ” FERET (Face Recognition Technology) Recognition Algorithm Development and Test Results”, October 1996. Army Research Lab technical report 995.

Zitieren als

Afifi, Mahmoud, and Mostafa Korashy. "Eyeglasses shop: Eyeglasses replacement system using frontal face image." Proc. 4th Int'l Conf. Mathematics and Information Science (ICMIS). 2015.

Kompatibilität der MATLAB-Version
Erstellt mit R2015a
Kompatibel mit allen Versionen
Plattform-Kompatibilität
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Veröffentlicht Versionshinweise
1.0.0.2

update description

1.0.0.1

.

1.0.0.0

description updated
.
Links to the datasets were added