Researchers Develop Deep-Learning Method to Predict Daily Activities

Researchers from the School of Interactive Computing and the Institute for Robotics and Intelligent Machines developed a new method that teaches computers to “see” and understand what humans do in a typical day.

“This work is about developing a better way to understand people's activities, and build systems that can recognize people's activities at a finely-grained level of detail,” said Edison Thomaz, co-author and graduate research assistant in the School of Interactive Computing. “Activity tracking devices like the Fitbit can tell how many steps you take per day, but imagine being able to track all of your activities – not just physical activities like walking and running. This work is moving toward full activity intelligence. At a technical level, we are showing that it's becoming possible for computer vision techniques alone to be used for this.”


Want to receive more content like this in your inbox?