The information that can be gained through vision is important to how we interact with our environment. Understanding vision in the broadest sense not only has implications for health and medicine, but it also informs how to make best use of visual technologies and how to design devices that can process visual information to expand their abilities.
That makes vision science more interdisciplinary than many people might think, extending far beyond biology and human perception and into fields like artificial intelligence and advanced robotics. The Vision: Science to Application (VISTA) program at York University brings together researchers from all of these areas, encouraging partnerships that push the field forward.
“Human vision requires input from all sorts of different areas,” says vision scientist Niko Troje.
“We need psychologists who really understand not just the physiology of, and the neuroscience of the brain, but really what happens in the perceiving mind. But on the other hand we need engineers and computer science colleagues to implement the models that we develop about how the brain is processing complex information, such as objects or faces or whole people.”
Putting vision researchers together can lead to exciting new research paths that come naturally from everyday conversations.
“The project where we’re trying to use the brain as a teacher for AI systems really came about from a conversation with myself and my collaborator on this, Alona Fyshe at UAlberta, and we were were sort of joking a little bit about what would happen if you could actually upload expertise from a person directly into a machine,” adds computational neuroscientist Joel Zylberberg.
“And that’s been really fun chasing that — the sort of imagination towards actually making something work.”
Other collaborations at VISTA look at the biology of vision, and vision neuroscientist Jennifer Steeves teamed up with health scientist Lauren Sergio to study how sex affects visual processing.
“It turns out that females tend to outperform males at face recognition,” says Steeves, “and so our goal is to look at these known structures in the brain that process faces, and where mental rotation is performed, to see if there are differences in brain activation that reflect the behaviour that we’ve observed in the laboratory.”
VISTA researchers also partner with industry to further their goals. Human/computer vision scientist James Elder notes that he met collaborators at CrossWing Incorporated at the VISTA Innovation Symposium. They specialize in social robots that can work with people to get jobs done.
“When the pandemic hit we started talking about how that would be useful, and then that led to the concept of those robots actually being able to disinfect areas — which first of all is kind of a tedious task, but secondly it’s somewhat of a hazardous task so it’s a perfect task for robots to perform rather than humans,” says Elder.
“So all of these things are critical, you really have to bring all these levels of support together into a single ecosystem.”