Wednesday, July 10 2013
The tracking method automatically follows the movements of people within a nursing home using cues such as apparel color, person detection, trajectory, and facial recognition.
Carnegie Mellon University has developed a method for tracking the locations of multiple individuals in complex, indoor settings using a network of video cameras. The method was able to automatically follow the movements of 13 people within a nursing home, even though individuals sometimes slipped out of view of the cameras. The method used multiple cues from the video feed including apparel color, person detection, trajectory, and facial recognition.
The performance of the Carnegie Mellon algorithm significantly improved on two of the leading algorithms in multi-camera, multi-object tracking. It located individuals within one meter of their actual position 88 percent of the time, compared with 35 percent and 56 percent for the other algorithms. These tracking techniques would be useful in airports, public facilities, and wherever security is a concern.