Related Experiment Video
Updated: Jul 30, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Published on: November 2, 2012
Object perception as Bayesian inference
Daniel Kersten1, Pascal Mamassian, Alan Yuille
1Department of Psychology, University of Minnesota, Minneapolis, Minnesota 55455, USA. kersten@umn.edu
Abstract:
We perceive the shapes and material properties of objects quickly and reliably despite the complexity and objective ambiguities of natural images. Typical images are highly complex because they consist of many objects embedded in background clutter. Moreover, the image features of an object are extremely variable and ambiguous owing to the effects of projection, occlusion, background clutter, and illumination. The very success of everyday vision implies neural mechanisms, yet to be understood, that discount irrelevant information and organize ambiguous or noisy local image features into objects and surfaces. Recent work in Bayesian theories of visual perception has shown how complexity may be managed and ambiguity resolved through the task-dependent, probabilistic integration of prior object knowledge with image features.
Related Concept Videos
Perception
Bottom-up processing begins at the sensory level, where receptors detect external environmental stimuli. These could include the tactile sensation of...
Depth Perception and Spatial Vision
Gestalt Principles of Perception
Factors Affecting Perception
An illustrative example of a perceptual set is the scenario where an airline pilot told...
Perceptual Constancy
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...
Introducing Social Perception

