LIFE Tags organizes over 4 million images from the LIFE magazine archives into an interactive encyclopedia using machine learning. Published weekly between 1936 and 1972 and monthly from 1978 to 2000, LIFE magazine was the most popular photojournalism magazine in the United States. Our experiment brings this iconic magazine to life.
With machine learning, we classified millions of images automatically into a catalogue format based on thousands of labels. For this project, we used Google’s Image Content-based Annotation (ICA) algorithm to generate labels based on image pixels. It is based on a deep neural network used in Google photo search that has been trained on millions of images and labels to recognize categories for labels and pictures.
You can easily navigate the LIFE magazine photo archive by browsing through the image categories and labels. A new random layout is generated at each visit, with a various choice of key images and titles. We clustered labels into categories using the nearest neighbor algorithm, which finds related labels based on image feature vectors. The ICA algorithm provides digital information for each image, which we translated into keywords, compared and grouped together.
Each image has multiple labels linked to the elements that are recognized. Click to view the full-size image and the dotted lines will show you where the relevant elements are located.
All labels have been automatically linked with their WIKIPEDIA definition to provide additional context.