*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
University of Minnesota’s Nikos Papanikolopoulos presents “Vision-Based Monitoring of Behavioral Disorders” as part of the IRIM Robotics Seminar Series. The event will be held in the TSRB Banquet Hall from 12-1 p.m. and is open to the public.
Abstract
This work involves algorithms to assist with the early diagnosis of children who are at risk of developing behavioral disorders. Previous research has indicated that two critical areas of behavioral investigation for use in identifying at-risk children have been abnormalities in motor activities and emotional range displays, especially of the face. Motor abnormalities are based on the observation that motor control involves the circuits of the brain associated with dopamine; these are also implicated in behavioral disorders. Many different disorders share the observation of disruption in the emotional range regulation, so facial expressions are included in the study.
To date, assessments of motor and emotional range have been done by the experts who view and rate videos of an individual. However, these expert, subjective ratings limit the analysis of behavioral conditions to only a narrow range of behaviors, work only for small populations of individual subjects, and are both costly and dependent on the observer's particular expertise. In order to enable wider population screening, automation is required. Innovative ways of capturing and quantifying the expertise of experts are accompanied by metrics for assessing the evolution of the behavior. In addition, new computational tools support evaluation of the effectiveness of interventions.
Bio
Nikolaos P. Papanikolopoulos, an IEEE Fellow, received a Diploma degree in electrical and computer engineering from the National Technical University of Athens, in Greece, in 1987, a M.S.E.E. in electrical engineering from Carnegie Mellon University, in 1988, and a Ph.D. in electrical and computer engineering from Carnegie Mellon University, in 1992. Currently, Papanikolopoulos is a Distinguished McKnight University Professor in the Department of Computer Science at the University of Minnesota and director of the Center for Distributed Robotics and SECTTRA. His research interests include computer vision, sensors for transportation applications, robotics, and control. He has authored or coauthored more than 350 journal and conference papers in the above areas, including 70 refereed journal papers.