Title
Visual Target Selection Emerges from a Bio-inspired Network Topology
Abstract
The orientation of sensors toward regions of interest of the environment is an important motor activity, monitored by ancient structures of the brain-stem. Particularly, the superior colliculus is known to be deeply involved in visual saccadic behavior. Target selection relies on various hints including exogenous information about the nature and the position of candidate targets and endogenous information about current motivations. We present a model of the collicular structure based on biological data, the specificity of which is related to the homogeneity of the underlying substratum of computation. This makes it more suitable to process massive visual flows on a distributed architecture, as it could be requested in a realistic task in autonomous robotics. The present model is restricted to the exogenous part of the visual pathway, from the retina to the superior colliculus. A realistic behavior for the selection of exogenous targets is reported here.
Year
DOI
Venue
2010
10.1007/978-3-642-27534-0_21
Studies in Computational Intelligence
Keywords
Field
DocType
Superior colliculus,Dynamic neural field,Visual attention,Ocular saccades
Superior colliculus,Computer vision,Motor activity,Computer science,Logical data model,Network topology,Visual attention,Artificial intelligence,Saccadic masking,Robotics
Conference
Volume
ISSN
Citations 
399
1860-949X
1
PageRank 
References 
Authors
0.37
5
3
Name
Order
Citations
PageRank
Wahiba Taouali120.73
Nicolas P. Rougier210614.78
Frédéric Alexandre38215.94