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Ontario Tech acknowledges the lands and people of the Mississaugas of Scugog Island First Nation.

We are thankful to be welcome on these lands in friendship. The lands we are situated on are covered by the Williams Treaties and are the traditional territory of the Mississaugas, a branch of the greater Anishinaabeg Nation, including Algonquin, Ojibway, Odawa and Pottawatomi. These lands remain home to many Indigenous nations and peoples.

We acknowledge this land out of respect for the Indigenous nations who have cared for Turtle Island, also called North America, from before the arrival of settler peoples until this day. Most importantly, we acknowledge that the history of these lands has been tainted by poor treatment and a lack of friendship with the First Nations who call them home.

This history is something we are all affected by because we are all treaty people in Canada. We all have a shared history to reflect on, and each of us is affected by this history in different ways. Our past defines our present, but if we move forward as friends and allies, then it does not have to define our future.

Learn more about Indigenous Education and Cultural Services

December 1, 2010

Speaker: Dr. Babak Taati, Research Associate, Intelligent Assistive Technology and Systems Lab, University of Toronto and Toronto Rehabilitation Institute

Title: Computer Vision Technologies to Promote Independent Living for the Elderly

Abstract: Improved medical care and the aging of the baby boomer generation have resulted in the increasing size and proportion of the world's elderly population. With the greying population, the prevalence of health issues associated with old age is also growing. The resulting cognitive or physical impairments often lead to the loss of independence among the elderly. Given a choice, many older adults prefer to live independently as long as possible. Such aging-in-place reduces healthcare costs in providing infrastructure and care while keeping the elderly happy, independent, and socially connected. This talk will be on intelligent assistive technologies that aim at enabling the elderly to live safely in their place of choice for as long as possible. In particular, the talk will focus on employing computer vision and machine learning techniques in two fronts: the first is the automatic detection of dangerous situations such as falls and emergency response. The second is video analysis methods to automate the process of product design usability assessment and to facilitate improved environmental design.

Biography: Babak Taati is a research associate in the Intelligent Assistive Technology and Systems Lab at the University of Toronto and the Toronto Rehabilitation Institute, where he develops and applies computer vision and machine learning algorithms in assistive and rehabilitation technology applications. Prior to joining UofT/TRI, he worked on 3D urban reconstruction from aerial images as lead computer vision scientist at Feeling Software. He completed his Ph.D. on object recognition and pose acquisition in range data at Queen's University and in collaboration with MDA Space Missions and the Canadian Space Agency. Results from his PhD research were used in a real-time pose acquisition and satellite tracking prototype developed at MDA Space Missions.