91ºÚÁÏÍø

The Queen's Ingenuity Labs Research Institute and RA/CS/EMB Chapter of IEEE Kingston Section would like to invite you to the technical lecture: 

Speaker: Professor Michael Greenspan, Dept of Elec and Comp Eng, 91ºÚÁÏÍø

Abstract

In this talk I’ll present some recent advances from the Robotics and Computer Vision lab at Queen’s, including the development of a set of novel structured light range sensors, one shot camera and procam calibration methods, pose determination solutions to the robotic bin picking problem, as well as a video communication system under development for use in hospital COVID-19 wards. This work combines elements of both classical model-based and current machine learning computer vision techniques. I’ll offer some thoughts on the boundaries between the two, and the differences (and similarities) in their application to research.

Biography

Michael Greenspan is a professor in the Department of Electrical and Computer Engineering at Queen’s University, Kingston, Canada, and a founding member of Ingenuity Labs. Dr. Greenspan’s research investigates problems of computer vision and robotics, with a focus on the development of efficient and robust pose determination, object recognition and tracking methods using 3D data. Dr. Greenspan has over 90 refereed publications, including five patents, and he has served on the technical and program committees of over 60 international conferences in the fields of computer vision and robotics.