I am currently evaluating capabilities of IBM Watson Visual Recognition service to recognize faces. So that System should identify the each person that we have trained. Individuals may come with different clothes, and other possible variations. But system should identify each individual by looking at each face.
As per IBM, IBM visual recognition do not support face recognition but only face detection.
Face Recognition: Visual Recognition is capable of face detection (detecting the presence of faces) not face recognition (identifying individuals).
Can we use the custom classifiers by adding different types of images for each individuals?
What is the significant pre/post-work from the developer to get at least 90% accuracy ?
Matt Hill posted a great reply to this similar question on dW Answers. Here's what he had to say:
It is possible to train a custom classifier to try to identify people's faces. It might help to use the face detection service as a preprocessor to give you bounding boxes around faces, and use them to crop the images submitted for custom classification. However, the VR custom learning engine is not optimized for face identification, and I would not expect the results to be as accurate as a system that is designed specifically for face recognition.
The issue is that human faces are typically very similar to each other in with respect to the wide set of features that were trained in learning the basis of the system, which needed a very broad exposure to many types of scenes and objects.