The fundamental goal of perception is to aid in the achievement of behavioral objectives. This requires extracting and communicating useful information from noisy and uncertain sensory signals. At the same time, given the complexity of sensory information and the limitations of biological information processing, it is clear that some information must be lost or discarded in the act of perception. Under these circumstances, what constitutes an `optimal' perceptual system? This talk will introduce rate-distortion theory (originally developed by Shannon) as the normative framework for understanding perception as a rational, but limited system. I will argue that the framework represents an important advance over the alternative computational framework offered by Bayesian inference. Experimental data will be presented from several domains (as time permits) including color perception, absolute identification, visual working memory, and haptic memory.
Event Details
Beyond Bayesian perception: Rate-distortion theory as a normative framework for understanding human perception
- Event Date: February 22, 2016
- Event Start Time: 12:00 PM
- Event End Time: 1:30 PM
- Event Location: Drexel University, Department of Psychology
- Event Type: Human and Computer Vision Series
- Event Semester: Spring 2016
- Event Contact: Dr. Chris Sims
- Event Extra info: <a href="http://drexel.edu/coas/faculty-research/faculty-directory/ChrisSims/">Dr. Chris Sims</a>