[12-26] Computer Vision for Active and Assisted Living

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Title:        Computer Vision for Active and Assisted Living
Speaker:  Lili Tao
                 Associate Professor in Machine Vision
                 the University of the West of England (UWE), U.K.
Time:       10:00am, Dec. 26, Tuesday, 2017
Venue:      Lecture Room of Collaborative Innovation Lab of ISCAS
                1st Floor of Northern Entrance, No.4 Building

          Intelligent visual monitoring has received a great deal of attention in the past decade, due to increased interest in smart healthcare systems in the home environments. Although a wide variety of sensing technologies can be used in in-home assistive systems, visual sensors have the potential to address several limitations of current systems: they do not require the user to wear them and they are able to simultaneously detect multiple events. Supporting an active and independent life style at home has become a prominent concern in modern society. Active and Assisted Living systems (AAL) support an independent and healthy lifestyle for individuals, particularly beneficial for the elderly and disabled.
          In this talk, we will discuss the problems and recent solutions associated with the development of AAL systems for real life settings.
          Lili Tao is an Associate Professor in Machine Vision at the University of the West of England (UWE), UK. She is also an Honorary Researcher at the University of Bristol. Before joining UWE, she was a Postdoctoral Research Associate at the University of Bristol (from 2013 to 2017). While there, she worked on the SPHERE project, applying computer vision techniques to help diagnosing and managing health and well-being conditions in home-based environments. Before that, she received a PhD degree (2013) from the University of Central Lancashire, UK. Her PhD research was focused on recovering the 3D non-rigid object and camera motion from a monocular video sequence.