From Low-level Sensors to High-level Intelligence: Activity Recognition Links the Knowledge Food Chain
published: July 22, 2009, recorded: July 2009, views: 8184
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Sensors provide computer systems with a window to the outside world. Activity recognition "sees" what is in the window to predict the locations, trajectories, actions, goals and plans of humans and objects. Building an activity recognition system requires a full range of interaction from statistical inference on lower level sensor data to symbolic AI at higher levels, where prediction results and acquired knowledge are passed up each level to form a knowledge food chain. In this talk, I will give an overview of activity recognition and explore its relation to other fields, including planning and knowledge acquisition, machine learning and Web search. I will also describe its applications in assistive technologies, security monitoring and mobile commerce.
Download slides: ijcai09_yang_fllshli_01.ppt (8.3 MB)
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