Department of Occupational Science and Occupational Therapy (University of Toronto) and the Toronto Rehabilitation Institute
Michael Belshaw is a Research and Software Developer in the Intelligent Assistive Technology and Systems Laboratory. Michael holds a Masters of Applied Science, Computer Engineering (Computer Vision) from Queen's University (Kingston).
As a Computer Vision Researcher at the Robotics and Computer Vision Laboratory at Queen's University, Michael worked on a multidisciplinary team developing "Fast Track". This research was part of a collaborative project with MDA Space Missions, Ryerson University and the University of Toronto. Michael's thesis focused on the design and development of a high speed Iterative Closest Point tracker on a FPGA platform. This tracking device is to be used for autonomous remote satellite capture and repair in space. Reprogrammable hardware was configured for visual 3D object tracking and integration with components for rectification and stereo extraction.
As the Chief Vision Scientist at xuuk Inc., Michael worked in the field of Human Computer Interaction, designing and developing algorithms for human eye contact sensing. Equipped with sensors designed to analyze the human eye, this technology can determine a person's gaze and thus provide precise, accurate measurements of the response of a target audience (e.g. for advertising or statistics).
Prior to joining IATSL, Michael worked as a Vision Specialist in the Department of Biology at Queen's University where he developed a software polar bear detector for research in the Arctic. This unique visual detector will enable researchers to discreetly study and track polar bears, thus eliminating the more invasive "capture and release" methods currently used to monitor, tag and track bears.
Michael's interest in robotic intelligence began with his design and development of an autonomous, interactive, game-playing robotic arm for which he won the IEEE Presidential Scholarship at the Intel International Science and Engineering Fair in 1999.
Currently, Michael is working with IATSL on the Intelligent Personal Emergency Response (PERS) and Fall Detection System. This fall detector improves personal safety by allowing intelligent monitoring of anyone who may need assistance in their environment. When triggered by an emergency, this assistive technology can help by interacting with the user through voice dialogues and immediately connect the user to proper human support channels such as medical assistance operators, neighbours, family or friends.
Michael S. Belshaw and Michael A. and Greenspan. A High Speed Iterative Closest Point Tracker on an FPGA Platform. IEEE International Workshop on 3-D Digital Imaging and Modeling (3DIM), Japan, Oct.2009.