THE ROLE OF LATEST FIXATIONS ON ONGOING VISUAL SEARCH
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THE ROLE OF LATEST FIXATIONS ON ONGOING VISUAL SEARCH

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The aim of the study is to understand the selection process, that modulates the exploration mechanism, during the execution of a high cognitively demanding task. The main purpose is to identify the ...

The aim of the study is to understand the selection process, that modulates the exploration mechanism, during the execution of a high cognitively demanding task. The main purpose is to identify the mechanism competition mechanism between top-down and bottom-up. We developed an adaptive system trying to emulate this mechanism.

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    THE ROLE OF LATEST FIXATIONS ON ONGOING VISUAL SEARCH THE ROLE OF LATEST FIXATIONS ON ONGOING VISUAL SEARCH Presentation Transcript

    • THE ROLE OF LATEST FIXATIONS ON ONGOING VISUAL SEARCH A MODEL TO EVALUATE THE SELECTION MECHANISM Giacomo Veneri, Pamela Federighi,Francesca Rosini, Elena Pretegiani, Antonio Federico, Alessandra Rufa Eye tracking & Vision Applications Lab (EVA Lab) Department of Neurological Neurosurgical and Behavioral Science University of Siena, Italy07/01/13 www.evalab.unisi.it 1
    • Outline• Top-Down vs Bottom-Up on ongoing visual search• Efficiency on Visual search• (Bayesian) Model on visual search07/01/13 www.evalab.unisi.it 2
    • Task  “Visual Search depends on sensory, perceptual and cognitive processes” [colby 2009]  Il TMT misuar la capcità di esplorare ed eseguire una sequenza in modo corretto  TMTB è un mappa viariante in cui i target diventano distrattori [Wolwer 2003]07/01/13 www.evalab.unisi.it 3
    • Mathematical Method Fixations07/01/13 www.evalab.unisi.it 4
    • Direction vs Previous fixations In order to test an overall validity of the model, we calculated for each test the DEMINFIX(T) – DEMINFIX and the DEMAXFIX(T) – DEMAXFIX.Figures show that saccade direction take in consideration mainly fixations of last 1000ms (1s).07/01/13 www.evalab.unisi.it 5
    • 07/01/13 www.evalab.unisi.it 6
    • Model07/01/13 www.evalab.unisi.it 7
    • Human vs Machine07/01/13 www.evalab.unisi.it 8
    • Conclusion• We found significant differences among tasks and a correlation between the efficiency (time elapsed) to explore the task and the ability to inhibit the BAF.• The command constraint (goal-driven) which is modulated by the image salience versus BAF.• The selection mechanism that drives this competition. Further works will be directed to evaluate the relation between the BAF and the inhibition of return.07/01/13 www.evalab.unisi.it 9
    • Conclusion• We found significant differences among tasks and a correlation between the efficiency (time elapsed) to explore the task and the ability to inhibit the BAF.• The command constraint (goal-driven) which is modulated by the image salience versus BAF.• The selection mechanism that drives this competition. Further works will be directed to evaluate the relation between the BAF and the inhibition of return.07/01/13 www.evalab.unisi.it 9