Connectionist models of Figure-Ground Segregation (Problems?)

[Frank Kelly]

Hello,
	I am doing a project on Nonlinear Coupled Oscillators applied to
Figure-Ground Segregation. Current models I have examined are included
below my mail.sig.

Basically the question I would like to pose is the following:

Although all of these models 'solve' figure-ground segregation to some
degree, can anyone say which model is 'best' and what crtieria can we
base this upon?

e.g. 
One of the key criteria for my project is speed, so what I would be
interested in knowing is:

	Which model is fastest and/or does any model approach the
	speed at which the human visual system segregates figure and ground.

Other criteria would be :
	* Resistance to Noise
	* Biological Plausibility
	* Model Complexity (e.g. does the neurons model allow for orientation
	selectivity, does the model require full connectivity between all
	nodes)
	*Use of attentional mechanisms

I would appreciate any light people could throw on this subject of
finding a 'best' model, especially experimental results/papers.
		
BTW, If anyone knows of any other systems (or has comments to make on any of
the above systems) I would be grateful if you could contact me.

Many Thanks in advance,

--Frank Kelly

=  Frank.Kelly at cs.tcd.ie  |  AI group, Dept. of Computer Science,   =
=  Work: +353-1-608 1800  |  Trinity College, Dublin 2. Ireland.    =
=  	WWW : http://www.cs.tcd.ie/www/kellyfj/kellyfj.html	    =


So far  I have found the following systems:
--------------------------------------------

[Von der Malsburg & Schneider 86]
	Von der malsburg, C., and W. Schneider A neural Cocktail-Party
	Processor in Biological Cybernetics 54, 29-40 (1986) 

[Von der Malsburg & Buhmann 92]
	Von der Malsburg, C., and J. Buhmann Sensory Segmentation with
	coupled neural oscillators in Biological Cybernetics 67, 233-242 (1992)

[Sompolinsky et al 90]
	Sompolinsky, H., Golomb, D., and D. Kleinfeld Global processing
	of visual stimuli in a neural network of coupled oscillators in
	Proceedings of the National Academy of Sciences, USA Vol.87, 
	pp.7200-7204, September 1990.

[Sejnowski & Hinton 87]
	Sejnowski, T.J., and G.E. Hinton Separating Figure from Ground
	with a Boltzmann Machine in (Arbib 87)

[Pabst et al. 89]
	Pabst, M., H.J. Reitboeck, and R. Eckhorn A model of Preattentive region
	definition based on texture analysis in (Cotterill 89)

[Konig et al. 92]
	Konig, P., Janosch, B., and T.B. Schillen Stimulus-Dependent
	Assembly Formation of Oscillatory Responses : III. Learning in Neural
	Computation 4, 666-681 (1992)

[Kammen et al. 89]
	Kammen, D.M., P.J. Holmes, and C. Koch Cortical Architecture and
	Oscillations in Neuronal Networks : Feedback vs. Local Coupling in 
	(Cotterill 89)

[Grossberg & Somers 91]
	Grossberg, S., and D. Somers Synchronized oscillations during
	cooperative feature linking in a cortical model of visual perception in
	Neural Networks Vol. 4 pp. 453-466

[Fellenz 94]
	Fellenz W.A. A Neural Network for Preattentive Perceptual Grouping in 
	Proceedings of the Irish Neural Networks Conference 1994
	Univeristy College Dublin, Sept.12-13, 1994

[Eckhorn et al 89]
	Eckhorn, R., H.J. Reitboeck, M. Arndt, and P.Dicke A Neural
	Network for feature linking via synchronous activity in (Cotterill 89)

[Yamaguchi & Hiroshi 94]
	Yamaguchi, Y., and S. Hiroshi Pattern recognition with figure-ground 
	seperation by generation of coherent oscillations in Neural Networks 
	Vol.3, 1994, 	pp.153-170

[Campbell and Wang 94]
	Campbell, S., and D. Wang Synchronization and Desynchronization
	in a Network of Locally Coupled Wilson-Cowan Oscillators in Technical
	Report OSU-CISRC-8/94-TR43, Lab for AI Research, Dept. of Computer and
	Information Science and Center for Cognitive Science, The Ohio State 
	University, Columbus, Ohio 43210-1277, USA

[Sporns et al. 91]
	Sporns, O. Tononi, G. and G.M. Edelman Modeling perceptual
	grouping and figure-ground segregation by means of active reentrant
	connections in Proc. Natl. Acad. Sci. USA Vol.88 oo.129-133, January 
	1991

n.b.
[Cotterill 89]	
	Cotterill, R.M.J. Models of Brain Function 1989