I want to do facial recognition on wide varieties of images captured at various ages of my family members. Below are some of the questions I have.
- If a person uses glasses of different types, do I need to feed images with each glasses type in the training dataset ? What if the eyes are not visible after wearing sunglasses. ?
- There are many pics which ranges from childhood to current age of approx 30. Do I need to train my model with pics of various ages to get good accuracy ?
- Do I need to align the images of train dataset for better accuracy ?
- Do I need to crop the background of the images in the training dataset just to keep the faces OR background doesn't matter ?
The idea behind my requirement is to scan through all the images on my hard disk (around 100 GB images) and classify the images in different folders for each person. I know similar thing is done on iphone and other mobile phones but I wanted to do it for the offline images stored on my external hard disk.
I was exploring facenet model from google, opencv face recognition. But stuck in the first step of dataset creation.