Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

This paper investigates how the visual areas of the brain may learn to segment the bodies of humans and other animals into separate parts. A neural network model of the ventral visual pathway, VisNet, was used to study this problem. In particular, the current work investigates whether independent motion of body parts can be sufficient to enable the visual system to learn separate representations of them even when the body parts are never seen in isolation. The network was shown to be able to separate out the independently moving body parts because the independent motion created statistical decoupling between them.

Original publication

DOI

10.1016/j.visres.2011.01.016

Type

Journal article

Journal

Vision Res

Publication Date

25/03/2011

Volume

51

Pages

553 - 562

Keywords

Brain, Human Body, Humans, Models, Neurological, Motion Perception, Recognition (Psychology), Visual Pathways, Visual Perception