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An algorithmic implementation of expert object recognition in ventral visual pathway

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dc.contributor.authorBaek, Kyungim, author
dc.date.accessioned2007-01-03T07:44:50Z
dc.date.available2007-01-03T07:44:50Z
dc.date.issued2002
dc.description.abstractUnderstanding the mechanisms underlying visual object recognition has been an important subject in both human and machine vision since the early days of cognitive science. Current state-of-the-art machine vision systems can perform only rudimentary tasks in highly constrained situations compared to the powerful and flexible recognition abilities of the human visual system. In this work, we provide an algorithmic analysis of psychological and anatomical models of the ventral visual pathway, more specifically the pathway that is responsible for expert object recognition, using the current state of machine vision technology. As a result, we propose a biologically plausible expert object recognition system composed of a set of distinct component subsystems performing feature extraction and pattern matching. The proposed system is evaluated on four different multi-class data sets, comparing the performance of the system as a whole to the performance of its component subsystems alone. The results show that the system matches the performance of state-of-the-art machine vision techniques on uncompressed data, and performs better when the stored data is highly compressed. Our work on building an artificial vision system based on biological models and theories not only provides a baseline for building more complex, end-to-end vision systems, but also facilitates interactions between computational and biological vision studies by providing feedback to both communities.
dc.format.mediumdoctoral dissertations
dc.identifier2002_Fall_Baek_Kyungim.pdf
dc.identifierETDF2002100003COMS
dc.identifier.urihttp://hdl.handle.net/10217/60538
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relationCatalog record number (MMS ID): 991016290779703361
dc.relationTA1634.B345 2002
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subject.lcshComputer vision
dc.subject.lcshPattern recognition systems
dc.titleAn algorithmic implementation of expert object recognition in ventral visual pathway
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineComputer Science
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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