Facebook (NASDAQ:FB) is trying to close the gap between humans and computers in facial recognition as the company says it has developed a technology that recognizes whether two different images are displaying the same face -- an ability that comes very close to replicating human ability to make the distinction. The new technology, called DeepFace, is claimed to be 97.25 percent accurate, reducing the margin of error with current state-of-the-art technology by more than 25 percent. According to Facebook, DeepFace is closely approaching human-level performance, which has scored 97.5 percent in the same standardized test. "In modern face recognition, the conventional pipeline consists of four stages: detect align represent classify," Facebook said in a research paper, released last week. "We revisit both the alignment step and the representation step by employing explicit 3D face modeling in order to apply a piecewise affine transformation, and derive a face representation from a nine-layer deep neural network."
In this tutorial, we'll see how we can create a python program that will detect emotion on a human face. This might be interesting if you want to do things like emotion detection using python, or if you're training machine learning systems to read human emotions. We're going to create a program that takes an image as an input and outputs a list of human emotions that the image invokes. To do this, we're going to use a package called Deepface. Deepface is an open-source face recognition attribute analysis framework that was created for python.
Uploading dozens of photos and tagging each one on Facebook can be tedious, and it appears the social network knows this. It recently created an algorithm that identifies faces'as accurately as a human' and offers tag suggestions which the user can accept, or reject. The technology - called DeepFace - was first showcased last March, but the site has now started rolling out the automatic tagging tool to select users. Facebook's DeepFace technology uses a 3D model to virtually rotate faces so that are facing the camera. DeepFace uses technology designed by an Israeli startup called face.com.
Recognition of the face as an identity is a critical aspect in today's world. Facial identification and recognition find its use in many real-life contexts, whether your identity card, passport, or any other credential of significant importance. It has become quite a popular tool these days to authenticate the identity of an individual. This technology is also being used in various sectors and industries to prevent ID fraud and identity theft. Your smartphone also has a face recognition feature to unlock it.
Have you noticed anything interesting the last time you uploaded a picture on Facebook? Perhaps you picked up on the fact that sometimes Facebook tries to tag your friends and family for you. Welcome to DeepFace, Facebook's facial recognition system. If you're wondering why it's called DeepFace, it's because at its core, the system is based on a type of Artificial Intelligence (AI) called Deep Learning. AI is here, and it's changing the way that we interact with technology on a daily basis.