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Contour integration models predicting human behavior [Elektronische Ressource] / von Nadja Schinkel-Bielefeld

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Contour Integration Models PredictingHuman BehaviorNadja Schinkel-BielefeldJuly 2007Contour Integration Models PredictingHuman BehaviorVom Fachbereich fur¨ Physik und Elektrotechnikder Universit¨ at Bremenzur Erlangung des akademischen Grades einesDoktor der Naturwissenschaften (Dr. rer. nat.)genehmigte DissertationvonNadja Schinkel-Bielefeld, M.Sc.aus Bremen1. Gutachter: Prof. Dr. rer. nat. Klaus Pawelzik2. Gutachter: Prof. Dr. rer. nat. Gun¨ ter MeinhardtEingereicht am: 17. Juli 2007Datum des Kolloquiums: 15. August 2007AbstractContour integration is believed to be a fundamental process in object recognitionand image segmentation. However, its neuronal mechanisms are still not wellunderstood. Psychophysical experiments showed that humans are remarkablyefficient in integrating contours even if these are jittered or partially occluded.Therefore the brain requires a reliable algorithm for extracting contours fromstimuli. Several recent publications demonstrated that the brain often uses op-timal strategies to integrate sensory information. Hence in this thesis I want totackle the question which contour integration model describes human contourintegration best.Mathematically, contour ensembles can be characterized by a conditional linkprobability density between oriented edge elements, termed an association field.This association field can be used to generate contours or vice versa to extract acontour from a stimulus.

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Published 01 January 2007
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Language English
Document size 11 MB