[ACT-R-users] Vision: estimate distances and pattern extrapolation?

[Dario Salvucci]

David,

As far as I know, the Gaussian assumption in EMMA is probably still a reasonable one. But either way, I'm not sure how it would address your extrapolation problem. I suppose the timing of a saccade could be used as an indicator of length (with a very fast clock, probably faster than ACT-R's timing module). As Dan suggests, calculating this might be the best option, where the calculation is a surrogate for some other process (like past learning of distances) not explicitly represented in the model.

Good luck
Dario


On Mar 8, 2013, at 2:54 PM, David Reitter <reitter at psu.edu> wrote:

> All,
> 
> I wonder if you have some ideas on models that could describe pattern recognition or implicit distance estimation.
> 
> I am looking at an experiment that requires subjects to estimate the difference between two or more visible dots and extrapolate along line between them to foveate on a spot.  
> Alternatively, one could think of it as pre-attentive processing, recognizing the dots and extrapolating the pattern in one direction (and foveate on that spot):
> 
> 
> 
> 	. 		.		.		X
> 
> 
> (Dots . are shown, and X is where I want to foveate, without anything being shown there.)
> 
> 
> It seems that the standard vision module does not give me the angle or distance between two screen locations (or finsts), although I could of course calculate that if I had the coordinates.  The precision of the estimates is unclear, though.  Referring to the ACT-R 6 manual, I don't see how I would get coordinates or estimate distance.
> 
> As for the saccadic movement, EMMA would be a good reference point: "Given a saccade to a particular object, the model assumes that the landing point follows a Gaussian distribution around the center of the object. (...)"  (Salvucci, 2001)  - Is this assumption still state of the art?
> 
> (I don't care much for timing in my model.)
> 
> There are models of many visual tasks out there (reading, object recognition/WHAT system, eye-movement), but what models explain aspects of pattern recognition or at least distance estimation?
> 
> Thanks for your input.
> 
> 
> ====
> 
> Some related literature:
> 
> Halverson, An “Active Vision” Computational Model Of Visual Search
> http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA518836
> 
> Oleksiak et al, Distance Estimation Is Influenced by Encoding Conditions
> http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2847905/
> 
> Salvucci, An integrated model of eye movements and visual encoding [EMMA]
> http://www.sciencedirect.com/science/article/pii/S1389041700000152
> [and various preceding work listed there, 
> 
> 
> 
> -- 
> Dr. David Reitter
> Assistant Professor of Information Sciences and Technology
> Penn State University
> http://www.david-reitter.com 
> 
> 
> 
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______________________________________________________________
Dario Salvucci, Ph.D.
Professor & Associate Department Head for Undergraduate Affairs
Department of Computer Science
Drexel University
http://www.cs.drexel.edu/~salvucci/

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