The Center for Education and Research in Information Assurance and Security (CERIAS)

The Center for Education and Research in
Information Assurance and Security (CERIAS)
Center for Education and Research in Information Assurance and Security

Advancing Low-Power Computer Vision at the Edge

Research Areas: Artificial Intelligence and Machine Learning

Principal Investigator: Yung-Hsiang Lu

Learning-based computer vision requires vast amounts of computation passing information through many layers of neural networks. This project investigates how to improve energy efficiency of computer vision so that it can run on embedded systems, thus at the cameras, without transmitting video streams through networks. State-of-the-art computer vision aims to create general-purpose solutions that can recognize hundreds of classes of objects. In constract, this project creates much smaller neural networks that specialize on distingushing only a few types of objects. If more types need to be distinguished, this project creates hierarchies of neural networks and allow early termination when detected objects are not of interest. This project has already demonstrated significant reduction in energy consumption with negligible loss of accuracy.

Personnel

Other PIs: James Davis

Other Faculty: Neil Klingensmith and George Thiruvathukal (Loyola University Chicago)

Students: Abhinav Goel

Representative Publications

Keywords: computer vision, embedded system, energy efficiency, low power