Designers are often interested in learning how an existing space is used so new environments can be programmed appropriately – either to support current activities or make others more likely. Hauptmann, Yu, and Yang at Carnegie Mellon “have developed a[n] [improved] 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 . . . [people] even though individuals sometimes slipped out of view of the cameras. . . . [individuals were tracked using] multiple cues from the video feed: apparel color, person detection, trajectory and, perhaps most significantly, facial recognition.” This new tool has been tested in a real world setting “with camera views compromised by long hallways, doorways, people mingling in the hallways, variations in lighting and too few cameras to provide comprehensive, overlapping views.” The system developed by the researchers “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.” When this video-based research methodology becomes generally available, design researchers can use it to develop rich, useful data sets.
“Carnegie Mellon Method Uses Network of Cameras to Track People in Complex Indoor Settings.” 2013. Press release, Carnegie Mellon University, http://www.cmu.edu/news/stories/archives/2013/june/june11_maraudersmap.html