How many images for good face recognition
I can't find a good answer for this.
Currently, my own experiments tell me i need at least 500+ images (currently i'm even thinking 1000 images) to get reliable face recognition, with lots of variation in illumination/facial hair, pictures close to the screen, far way, head tilted to the left or right, up and down etc. I am taking the images from webcam.
Now i'm approaching 2 problems.
- I suspect that to much variation will generalize the image and not help at all anymore. There must be a limit of diminishing returns.
- It takes an awful long time to start and train the program (10 minutes?) with 3 people and about 500 images each. Total image size is about 20Mb, and a saved model is about 56000 Kbytes. Would saving and loading the model be quicker on startup?
I would have hoped i would be able to do with much less (i can but then it is not so reliable i would be able to use it in a commercial fashion anymore). I don't see much difference using either Eigen or Fisherfaces. But maybe i need to keep more components, currently only doing 10 for Eigen.
Thanks for your comments! atv
Just fyi, currently my datasets are not entirely even, i will make them all an even amount of images and retest.
This is a classical pattern recognition dilemma, nowadays with deep learning techniques the mass is typically more important - the more the better. If you don't have so much data then other methods might work as well (or even better).