Spring
semester, 2004
Instructor:
Mike Lewicki
Computer Science Department and
Center for the Neural Basis of Cognition
Carnegie Mellon University
Units: 9 (undergraduate) or 12 (graduate)
Days/Times: Tuesdays and Thursdays, 3:00 - 4:20
Location: 200 OSC (Old Student Center, 4902 Forbes Ave.)
Course Description
This course teaches advanced aspects of perception, scene analysis,
and recognition in both the visual and auditory modalities,
concentrating on the essential computational processes that allow us
and animals to behave in natural, complex environments. The goal of
this course is to teach how to reason scientifically about problems and
issues in perception and scene analysis, how to extract the essential
computational properties of those abstract ideas, and finally how to
convert these into explicit mathematical models and computational
algorithms. Throughout the course we examine important findings
from perceptual science that have provided key insights into the
function and organization of human and animal perceptual systems.
Specific topics include sensory coding, perceptual invariance, spatial
vision and sound localization, visual and auditory scene segmentation,
many aspects of attention, and approaches to recognition in natural
visual and auditory scenes.
Mathematical topics covered include Bayesian inference, information
theory, linear systems analysis, neural networks, independent component
analysis, and selected algorithms in computational vision and audition.
Prerequisites: 15-385, 85-370, or permission of the instructor.
Contact:
Mike Lewicki
lewicki@cs.cmu.edu
http://www.cs.cmu.edu/~lewickiOffice: Mellon Institute 115K, x8-3921
Other
links: