It appears that Carnegie Mellon computer scientists and other researchers have created a way to track the locations of multiple individuals in a complex, indoor setting in real time. What does this remind you of?
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. None of Potter's magic was needed to track them for prolonged periods; rather, the researchers made use of multiple cues from the video feed: apparel color, person detection, trajectory and, perhaps most significantly, facial recognition.
Multi-camera, multi-object tracking has been an active field of research for a decade, but automated techniques have only focused on well-controlled lab environments. The Carnegie Mellon team, by contrast, proved their technique with actual residents and employees in a nursing facility—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 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.
Usually, I restrict myself to science-fictional creations when writing articles for Technovelgy, but I hope readers will forgive me for noting that this technical accomplishment is a "Marauder's Map" brought to life from the pages of J.K. Rowling's Harry Potter books.
A System To Defeat AI Face Recognition
'...points and patches of light... sliding all over their faces in a programmed manner that had been designed to foil facial recognition systems.' - Neal Stephenson, 2019.
Smart TVs Are Listening!
'You had to live -- did live, from habit that became instinct -- in the assumption that every sound you made was overheard...' - George Orwell, 1948.
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A System To Defeat AI Face Recognition
'...points and patches of light... sliding all over their faces in a programmed manner that had been designed to foil facial recognition systems.'