Student Spotlight: The Future of Video Monitoring

Studying artificial intelligence, Can Gao explores ways computers can keep a watchful eye on human activity.

March 11 , 2008 - Can Gao, an INI graduate student (Athens MSIN), is conducting research in artificial intelligence. Under the supervision of senior system scientist, Alex Hauptmann, and system scientist, Datong Chen, Can has focused his master's thesis on unsupervised learning of human action.

Through his research, Can directs a computer to "watch" videos of humans and recognize activities that occur, such as kicking, punching and knocking over things. To do this, Can designs and implements machine-learning algorithms that allow a computer to distinguish different activities and classify them. His research could one day be used to detect when violent or dangerous acts occur on camera.

This research is useful for many environments that monitor activities, such as nursing homes where cameras are used to address falls and other health emergencies. As the senior population grows, clinicians and geriatric professionals need advanced technologies to support them in managing patients’ quality of life. Through Can's research, patients could be monitored better and effectively treated on time.

Can's current research relates significantly to his interest in machine learning. Can began the MSIN program at Athens Information Technology (AIT) in Greece, where he spent his first year. He enrolled in the INI exchange program to complete his second year of coursework and research in Pittsburgh, where he participates in the School of Computer Science's Informedia project. He previously conducted research on a related topic with Sofia Tsekeridou, assistant professor at AIT.

Contributed by Eunjung Yoon, MS18