article_snippet: Our method uses a deep convolutional network trained to directly optimize the embedding itself, rather than an intermediate bottleneck layer as in previous deep learning approaches,' Google researchers say. '
article_snippet: However, Google researchers went beyond simply verifying whether two faces are identical by also attaching a name to a face.
article_snippet: Google's system first clusters photos into a collection of similar faces .
article_snippet: Taking a classic facial recognition approach, Facebook researchers went as far as organizing the images into groups of faces that look the most similar or the most distinct.
article_snippet: The researchers used the software to build a 3D model of a face from a photo that can be rotated into the best position for an algorithm to begin searching for a match.
article_snippet: After creating a model, the team used a neural network that had been trained on a database of faces to try and match the face with one in a test database of more than 4 million images, containing more than 4,000 separate identities, each one labelled by humans.
article_snippet: The researchers used the software to build a 3D model of a face from a photo that can be rotated into the best position for an algorithm to begin searching for a match.
article_snippet: After creating a model, the team used a neural network that had been trained on a database of faces to try and match the face with one in a test database of more than 4 million images, containing more than 4,000 separate identities, each one labelled by humans.
article_snippet: Taylor Hatmaker at The Daily Dot, for example, said that Taylor Hatmaker at The Daily Dot recently tested the feature using an album of 15 photos.
article_snippet: None of the images had been shared previously, and Facebook identified and automatically tagged faces in eight of the photos.
highlights_snippet: System could be used to automatically recognise photos on Google+ . 