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A Survey of Sensor-based Activity Recognition: A Machine Learning Perspective
PhD Qualifying Examination Title: "A Survey of Sensor-based Activity Recognition: A Machine Learning Perspective" Mr. Hao HU Abstract: Automatic recognizing human activities is an important task which can support many applications, from context-aware computing to just-in-time information systems to assistive technology for the disabled. It is also a multidisciplinary research area draws from Machine Learning and AI, Machine Perception, Ubiquitous Computing, Human Computer Interaction, as well as psychology and sociology. Thus, human activity recognition has been drawing increasing interest for researchers in a variety of fields. We focus the two major components in activity recognition systems in this paper, the first is the sensing component and the other is the learning and inference component. In this article, we would survey some of the important works being pursued in these two components over the past few years. We would also discuss some other important research topics related to activity recognition that is nonetheless difficult to be categorized into progresses in the two major components. Finally, we would also try to discuss some problems that exist alongside which we could carry on in other future research directions. Date: Wednesday, 29 April 2009 Time: 11:00am-1:00pm Venue: Room 3501 lifts 25-26 Committee Members: Prof. Qiang Yang (Supervisor) Dr. Ke Yi (Chairperson) Prof. Lionel Ni Prof. Dit-Yan Yeung **** ALL are Welcome ****