The researchers are developing a system to enable
"Once you have robots that cooperate you can do all sorts of things," said Kilian Weinberger, associate professor of computer science, who is collaborating on the project with Silvia Ferrari, professor of mechanical and aerospace engineering, and Mark Campbell, the John A. Mellowes '60 Professor in Mechanical Engineering.
Their work, "Convolutional-Features Analysis and Control for Mobile Visual Scene Perception," is supported by a four-year, $1.7 million grant from the U.S. Office of Naval Research (ONR). The researchers will call on their extensive experience with computer vision to match and combine images of the same area from several cameras, identify objects and track objects and people from place to place. The work will require groundbreaking research, Weinberger said, because most prior work in the field has focused on analyzing images from just a single camera as it moves around. And often, Ferrari added, a camera that doesn't move at all. The new system will fuse information from fixed cameras, mobile observers and outside sources.
The mobile observers might include autonomous aircraft and ground vehicles and perhaps humanoid robots wandering through a crowd. They will send their images to a central control unit, which might also have access to other cameras looking at the region of interest, as well as access to the internet for help in labeling what it sees. What make of car is that? How do you open this container? Identify this person.
The system might notice a significant face, then track that face through the crowd, Weinberger suggested. In earlier work, Ferrari developed what might be described as a robot game of Marco Polo, where a team of hunters track targets through a complex environment.
Read more at: https://phys.org/news/2017-04-link-robots-surveillance-teams.html#jCp
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