UNIVERSITY OF TWENTE.

Alexander Hauptmann (Carnegie Mellon University, USA)

Video Information Extraction for Long Term Activity Analysis in Health Care

Analyzing human activity is the key to understand and search surveillance videos. I will discuss the current results from a study to utilize automatic human activities analysis to improve geriatric health care. Beyond just recognizing human activities observed on video, we mine a 25 day archive of observations in a nursing home, and link the observational results to medical records. This work explores the statistical patterns between a patient's daily activity and his/her clinical diagnosis.

Our main contribution is in developing and using an intelligent visual surveillance system based on efficient and robust activity analysis and a demonstration of the feasibility of exploiting long term human activity patterns though video analysis.

Presentation at SSR