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New NSF Grant: Cyber Infrastructure to Enable Computer Vision Applications at the Edge Using Automated Contextual Analysis

George K. Thiruvathukal receives $175,000 NSF grant to advance computer vision and software engineering practices on low-power edge devices and benefit society.

Computer Science Newsroom, George K. Thiruvathukal

• 1 min read
New NSF Grant: Cyber Infrastructure to Enable Computer Vision Applications at the Edge Using Automated Contextual Analysis
When segmented, the background of an image can tell a lot about what classes of objects are expected in the associated foreground via background-implies-foreground relationships.

This proposal enables low-power edge computers, such as mobile phones, drones, and Internet-of-Things devices, to benefit society. Computer vision is the technology to automatically analyze images and videos. Computer vision on these devices can keep humans safe, for example by spotting dangers in a factory or at a construction site. This project addresses two challenges that hamper practical adoption of computer vision on edge devices.

  • The first challenge is that current computer vision approaches require powerful computers, but these computers are too far away and have long response time.
  • The second challenge is that building complex software for computer vision is difficult.

This project provides software engineering support for emerging computer vision technologies. As a result of addressing these two challenges, computer vision on the edge can become feasible.

For additional details, see NSF Award Abstract #2104319

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