Face Recognition
Introduction
Face Recognition is one of the most important applications of computer vision,
which has attracted significant attention from both academia and industry.
One of the major frameworks that has been proposed for face recognition and
has produced promissing results is the Bag-of-Words (BoW) approach. In this research,
we explore how this general framework can be optimized for the task of face
recognition by evaluating different feature descriptors and different BoW
configurations. More specifically, we use automatic feature selection methods,
such as forward greedy and backward greedy, to choose a compact set of features
(e.g., descriptors, window locations, window sizes, dictionary sizes, etc.) that
can produce the highest accuracy.
Resources
Code
To be posted soon!
Database
Here you can find the database