The database was downloaded from the following website: http://aicip.eecs.utk.edu/wiki/UTKFace. Firstly, images were transformed to greyscale and the Viola-Jones algorithm was applied on randomly selected samples to extract face from the background. The principal component analysis was used to generate Eigen faces from the training set images. Training and testing set images were projected on Eigen faces and Euclidian distance was measured between each testing and training image. Gender and age of image from the testing dataset was determined based on the closest image from the training dataset.
-
Notifications
You must be signed in to change notification settings - Fork 2
kekastepanovic/Face-Gender-and-Age-Recognition-Using-Principal-Component-Analysis
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
Detecting gender and age based on the face image applying unsupervised machine learning
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published