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GRASP Special Seminar: Changhyun Choi, Georgia Institute Of Technology, "Visual Object Perception In Unstructured Environments"
Presenter: Changhyun Choi (Homepage)
Friday July 18, 2014 from 1:00pm to 2:00pm
* Alternate Location: Levine 307*
As robotic systems move from well-controlled settings to increasingly unstructured environments, they are required to operate in highly dynamic and cluttered scenarios. Finding an object, estimating its pose, and tracking its pose over time within such scenarios are challenging problems. Although various approaches have been developed to tackle these problems, the scope of objects addressed and the robustness of solutions remain limited. In this talk, I will present a robust object perception using visual sensory information, which spans from the traditional monocular camera to the more recently emerged RGB-D sensor, in unstructured environments. I will address four important challenges, such as significant clutter in backgrounds, objects with and without texture, object discontinuous cases during tracking, and real-time constraints, to robust 6-DOF object pose estimation and tracking that current state-of-the-art approaches have, as yet, failed to solve. Various object pose estimation and tracking examples will be shown with several applications in robotics.
Changhyun Choi is a Ph.D. candidate in the School of Interactive Computing, College of Computing at the Georgia Institute of Technology (Georgia Tech) in Atlanta, Georgia, USA. He is also affiliated with the Institute for Robotics and Intelligent Machines (IRIM) at Georgia Tech. He was a research intern in the Imaging Group of Mitsubishi Electric Research Labs (MERL) in Cambridge, Massachusetts, USA, an intern researcher at the Imaging Media Research Center (IMRC) at Korea Institute of Science and Technology (KIST), and an undergraduate researcher at the Intelligent Systems Research Center at Sungkyunkwan University in Korea. He holds a B.S. in Information and Communication Engineering from Sungkyunkwan University. His broad research interests are in visual perception for robotics, with a focus on object recognition and pose estimation, visual tracking, and 3D registration.