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Fall 2017 GRASP Seminar Series: Kris Kitani, CMU, “Wearable Sensing for Understanding, Assisting and Forecasting Human Activity”

December 8, 2017 @ 11:00 am - 12:00 pm


Wearable sensors such as action cameras and smartphones, can collect content-rich information that can be used to characterize human activities. In this talk,I will describe how wearable sensors can be used to understand, predict and assist human activity. First person vision systems (wearable cameras) are excellent for recognizing hand object manipulations. I will describe our recent work that can be used to automatically recognize first-person activities, understanding scene functionality and also predict into the future what a person will do. I will also describe how a wearable sensor — the smartphone — can be used as an assistive technology. I will present, NavCog, a smartphone based indoor navigation app that can be used to help people with visual impairments travel in new environments.


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Kris M. Kitani is an assistant research professor in the Robotics Institute at Carnegie Mellon University. He received his BS at the University of Southern California and his MS and PhD at the University of Tokyo. His research projects span the areas of computer vision, machine learning and human computer interaction. In particular, his research interests lie at the intersection of first-person vision, human activity modeling and inverse reinforcement learning. His work has been awarded the Marr Prize honorable mention at ICCV 2017, best paper honorable mention at CHI 2017, best technical paper at W4A 2017, best application paper ACCV 2014 and best paper honorable mention ECCV 2012.


December 8, 2017
11:00 am - 12:00 pm
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