<html><head><meta http-equiv="Content-Type" content="text/html charset=windows-1252"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">David,<div><br></div><div>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.</div><div><br></div><div>Good luck</div><div>Dario</div><div><br></div><div><br><div><div>On Mar 8, 2013, at 2:54 PM, David Reitter <<a href="mailto:reitter@psu.edu">reitter@psu.edu</a>> wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite">All,<br><br>I wonder if you have some ideas on models that could describe pattern recognition or implicit distance estimation.<br><br>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. <br>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):<br><br><br><br><span class="Apple-tab-span" style="white-space:pre"> </span>. <span class="Apple-tab-span" style="white-space:pre"> </span><span class="Apple-tab-span" style="white-space:pre"> </span>.<span class="Apple-tab-span" style="white-space:pre"> </span><span class="Apple-tab-span" style="white-space:pre"> </span>.<span class="Apple-tab-span" style="white-space:pre"> </span><span class="Apple-tab-span" style="white-space:pre"> </span>X<br><br><br>(Dots . are shown, and X is where I want to foveate, without anything being shown there.)<br><br><br>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.<br><br>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?<br><br>(I don't care much for timing in my model.)<br><br>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?<br><br>Thanks for your input.<br><br><br>====<br><br>Some related literature:<br><br>Halverson, An “Active Vision” Computational Model Of Visual Search<br><a href="http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA518836">http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA518836</a><br><br>Oleksiak et al, Distance Estimation Is Influenced by Encoding Conditions<br>http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2847905/<br><br>Salvucci, An integrated model of eye movements and visual encoding [EMMA]<br>http://www.sciencedirect.com/science/article/pii/S1389041700000152<br>[and various preceding work listed there, <br><br><br><br>-- <br>Dr. David Reitter<br>Assistant Professor of Information Sciences and Technology<br>Penn State University<br>http://www.david-reitter.com <br><br><br><br>_______________________________________________<br>ACT-R-users mailing list<br>ACT-R-users@act-r.psy.cmu.edu<br>https://mailman.srv.cs.cmu.edu/mailman/listinfo/act-r-users<br></blockquote></div><br><div apple-content-edited="true">
<div style="color: rgb(0, 0, 0); font-family: Helvetica; font-size: medium; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-align: -webkit-auto; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">______________________________________________________________<br>Dario Salvucci, Ph.D.<br>Professor & Associate Department Head for Undergraduate Affairs<br>Department of Computer Science<br>Drexel University<br><a href="http://www.cs.drexel.edu/~salvucci/">http://www.cs.drexel.edu/~salvucci/</a></div>
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