Given pictures with multiple features such as faces, can single AI algorithm detect all of them, or for better reliability is it preferred to use separate instances?

In other words I'm talking about attempt of finding all possible human faces on the same picture by a single neural network.

  • $\begingroup$ Yes, finding several faces (unknown number of them) on one image by one AI network. $\endgroup$
    – kenorb
    Aug 4 '16 at 13:41
  • $\begingroup$ @bpachev Yes, I've added appropriate tag. $\endgroup$
    – kenorb
    Aug 4 '16 at 21:00

AFAIK, normally detection algorithms work in a sub-window of the image and not the whole of it. For example, for a specific size and orientation you slide a sub-window on the image and extract sub-images. Then you apply your algorithm on every sub-image for detection and report the size-and-orientations with positive results.

You can have a single neural network for face detection in this case or you might want to have different detectors for different orientation or any other feature, that is your decision.

There is also the technique of Combining Classifiers by which you can improve the decision of single classifiers by combining them.

Ensemble Learning is another way in which your classifiers are not trained independently but rather together. In fact, the well-known object detector of Viola and Jones uses such a technique.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.