Manufacturing Engineering and Engineering Management
City University of Hong Kong
MEEM Seminar 0708_027
Recognition Technology in Eldercare
Abstract
Recognition Technology, as defined by L. Zadeh, refers to current or future systems that have the potential to provide a "quantum jump in the capabilities of today's recognition systems", and includes systems that incorporate new sensors, novel signal processing and soft computing. This talk concerns eldercare. One focus of our large interdisciplinary research effort is the creation of intelligent systems that use sensors to uncover patterns of activity helpful to caregivers, especially targeting mobility and cognitive impairment. After a brief overview, I will discuss how the engineering aspects of eldercare research perfectly fit the recognition technology framework. I will show applications of computational intelligence techniques, among others, applied to the sensing environment. The wealth of simple sensor data is just beginning to be mined for activity information on residents. Both feature display and processing will be highlighted. A major effort of our group! involves silhouette extraction and tracking with video sensors. A hierarchical fuzzy logic system is built to determine memberships in various states, followed by another set of rules to classify activities (early focus on fall detection). To better model the uncertainty in the calculations and rules, experiments extending the system to type 2 fuzzy logic are being conducted. The second major video activity deals with markerless motion capture for monitoring physical activity in elders.
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Event: |
MEEM Seminar 0708_027 |
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Date: |
29 May 2008 (Thursday) |
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Time: |
4:30 pm |
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Venue: |
MEEM Conference Room (B6619) |
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Speaker: |
Prof. James M. Keller |
About the Speaker
James M. Keller received the Ph.D. in Mathematics in 1978. He holds the University of Missouri CuratorsProfessorship in the Electrical and Computer Engineering and Computer Science Departments on the Columbia campus. He is also the R. L. Tatum Professor in the College of Engineering. His research interests center on computational intelligence: fuzzy set theory and fuzzy logic, neural networks, and evolutionary computation with a focus on problems in computer vision, pattern recognition, and information fusion including bioinformatics, spatial reasoning in robotics, geospatial intelligence, sensor and information analysis in technology for eldercare, and landmine detection. Dr. Keller has coauthored over 250 technical publications. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) for whom he has presented live and video tutorials on fuzzy logic in computer vision, is an International Fuzzy Systems Association (IFSA) Fellow, is a nation! al lecturer for the Association for Computing Machinery (ACM), is an IEEE Computational Intelligence Society Distinguished Lecturer, and is a past President of the North American Fuzzy Information Processing Society (NAFIPS). He received the 2007 Fuzzy Systems Pioneer Award from the IEEE Computational Intelligence Society. He finished a full six year term as Editor-in-Chief of the IEEE Transactions on Fuzzy Systems, is an Associate Editor of the International Journal of Approximate Reasoning, and is on the editorial board of Pattern Analysis and Applications, Fuzzy Sets and Systems, International Journal of Fuzzy Systems, and the Journal of Intelligent and Fuzzy Systems. He is currently the Vice President for Publications of the IEEE Computational Intelligence Society.
Enquiry: MEEM General Office (Tel: 2788 8420 Email: mego@cityu.edu.hk )