Face recognition and occlusion identification.
Goal of this project was to observe how occlusions and different emotional expressions impact face recognition process using Python language.
Source of face photos was Yale Faces database: http://cvc.cs.yale.edu/cvc/projects/yalefaces/yalefaces.html
Firstly, faces without occlusion were introduced:
Then, faces with different occlusions (glasses, lightning, face expression etc.).
Success rate was above 90%.