Post-doctoral position available in 360-degree imaging for navigation assistance for the visually impaired aims to leverage the benefits of head-worn, panoramic imaging systems to 1) safely guide users during intersection crossing to avoid veering, which can be dangerous and stressful, and 2) help them navigate the last few meters to doorways they wish to enter. Our proposed approach combines a machine learning strategy leveraging existing image datasets, possibly augmented by crowdsourcing, and iterative design of the feedback mechanisms. This project, funded by an NSERC grant, and in collaboration with Immervision, is informed by the team’s experience with sensor-based intersection-crossing assistance systems, and in developing the Autour app, which provides a real-time description of street intersections, public transport data, and points of interest in the user’s vicinity.
The successful candidate will lead the research and development activities, mentor students, supervise user tests with members of the visually impaired community, and contribute to publications related to the project.
Education/Experience: A PhD in electrical or computer engineering, computer science, or closely related field, with experience in image processing, machine learning, and mobile development. Preference will be given to applicants having demonstrated additional experience in human-computer interaction, assistive technologies, or crowdsourcing, and with a strong publication record.
Appointment will be through the Centre for Intelligent Machines. Further information and instructions for applying are available at the Employer Job Post link (URL) above.
January 15, 2020 (Negotiable)
December 16, 2019
EMPLOYER JOB POST
Human-Computer Interaction; Assistive Technology; Image Understanding