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H. Neumann and E. Mingolla
ABSTRACT
Recent developments in the neural computational modeling of perceptual grouping are described with reference to a newly proposed taxonomy to formalize mechanisms of spatial integration This notational framework and nomenclature is introduced in or der to clarify key properties common to all or most models while permitting unique attributes of each approach to be independently examined The strength of spatial integration in the models that are considered is always some function of the distances and relative alignments in perceptual space of the centers of units representing orien tational features or energy in a visual scene We discuss the signicance of variations of the constituents of an activation function for spatial integration and also consider the larger modeling framework in which this function is applied in each approach We also discuss the relationship of feedforward and feedback mechanisms and the issues of selforganization as core principles underlying the establishment of spatial integra tion mechanisms The relationship of the grouping models to models of other visual competencies is considered with respect to prospects for future research 
ECVision indexed and annotated bibliography of cognitive computer vision publications
This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1
The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
Computational neural models of spatial integration in perceptual groupingSite generated on Friday, 06 January 2006