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Winter 2020: The Ecological Approach to Visual Perception

Winter 2020: The Ecological Approach to Visual Perception

Course No:
EECS 598-007
Credit Hours:
3 credits
Instructor:
David Fouhey
Prerequisites:
Graduate standing in EECS or Robotics or permission of instructor

Specifically, we will explore (in no particular order): the perception of affordances and spatial layout; perception of and for manipulation; agents and how they exist in their environment; visual navigation; learning from demonstration and natural supervision; learning of physical models and dynamics; and learning of agency and intentionality. While the primary focus and assumed background knowledge is learning-based visual perception, readings will come from a wide variety of fields and students should be prepared to read out of their comfort zone.

This is a graduate-level course incorporating two components. The first is weekly group-driven reading and active discussion and debating of related work in robotics, computer vision, machine learning, and psychology. This will be a roughly even split between recent work and classics. The second are projects that put ideas from the first component to the test. These are semester-long projects, ideally interdisciplinary, that: find a particular problem; make a concrete hypothesis and experiments to test it; and execute them computationally using realistic data.

More info (pdf)