Neurophysiology of shape processing
Recent physiological findings are reviewed and synthesized into a model of shape processing and object recognition. Gestalt laws (e.g. good continuation, closure) and ‘non-accidental’ image properties (e.g. colinear terminating lines) are resolved in prestriate visual cortex, (areas V2 and V3) to su...
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Veröffentlicht in: | Image and vision computing 1993, Vol.11 (6), p.317-333 |
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creator | Perrett, D.I. Oram, M.W. |
description | Recent physiological findings are reviewed and synthesized into a model of shape processing and object recognition. Gestalt laws (e.g. good continuation, closure) and ‘non-accidental’ image properties (e.g. colinear terminating lines) are resolved in prestriate visual cortex, (areas V2 and V3) to support the extraction of 2D shape boundaries. Processing of shape continues along a ventral route through inferior temporal (IT) cortex where a vast catalogue of 2D shape primitives is established. Each catalogue entry is size-specific (±0.5 log scale unit) and orientation-specific (±45°), but can generalize over position (±150 degree
2). Several shape components are used to activate representations of the
approximate
appearance of one object type at one view, orientation and size. Subsequent generalization, first over orientation and size, then over view, and finally over object sub-component, is achieved in the anterior temporal cortex by combining descriptions of the same object from different orientations and views, through associative learning. This scheme provides a route to 3D object recognition through 2D shape description and reduces the problem of perceptual invariance to a series of independent analyses with an associative link established between the outputs. The system relies on parallel processing with computations performed in a series of hierarchical steps with relatively simple operations at each stage. |
doi_str_mv | 10.1016/0262-8856(93)90011-5 |
format | Article |
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2). Several shape components are used to activate representations of the
approximate
appearance of one object type at one view, orientation and size. Subsequent generalization, first over orientation and size, then over view, and finally over object sub-component, is achieved in the anterior temporal cortex by combining descriptions of the same object from different orientations and views, through associative learning. This scheme provides a route to 3D object recognition through 2D shape description and reduces the problem of perceptual invariance to a series of independent analyses with an associative link established between the outputs. The system relies on parallel processing with computations performed in a series of hierarchical steps with relatively simple operations at each stage.</description><identifier>ISSN: 0262-8856</identifier><identifier>EISSN: 1872-8138</identifier><identifier>DOI: 10.1016/0262-8856(93)90011-5</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>computational modelling ; object recognition ; pattern processing ; single-unit</subject><ispartof>Image and vision computing, 1993, Vol.11 (6), p.317-333</ispartof><rights>1993</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c367t-911a01674f0603bae971a94d794308cd0e7a57a46029274a423b7fa7ec80d02e3</citedby><cites>FETCH-LOGICAL-c367t-911a01674f0603bae971a94d794308cd0e7a57a46029274a423b7fa7ec80d02e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/0262-8856(93)90011-5$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,4024,27923,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Perrett, D.I.</creatorcontrib><creatorcontrib>Oram, M.W.</creatorcontrib><title>Neurophysiology of shape processing</title><title>Image and vision computing</title><description>Recent physiological findings are reviewed and synthesized into a model of shape processing and object recognition. Gestalt laws (e.g. good continuation, closure) and ‘non-accidental’ image properties (e.g. colinear terminating lines) are resolved in prestriate visual cortex, (areas V2 and V3) to support the extraction of 2D shape boundaries. Processing of shape continues along a ventral route through inferior temporal (IT) cortex where a vast catalogue of 2D shape primitives is established. Each catalogue entry is size-specific (±0.5 log scale unit) and orientation-specific (±45°), but can generalize over position (±150 degree
2). Several shape components are used to activate representations of the
approximate
appearance of one object type at one view, orientation and size. Subsequent generalization, first over orientation and size, then over view, and finally over object sub-component, is achieved in the anterior temporal cortex by combining descriptions of the same object from different orientations and views, through associative learning. This scheme provides a route to 3D object recognition through 2D shape description and reduces the problem of perceptual invariance to a series of independent analyses with an associative link established between the outputs. The system relies on parallel processing with computations performed in a series of hierarchical steps with relatively simple operations at each stage.</description><subject>computational modelling</subject><subject>object recognition</subject><subject>pattern processing</subject><subject>single-unit</subject><issn>0262-8856</issn><issn>1872-8138</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1993</creationdate><recordtype>article</recordtype><recordid>eNp9kElLAzEUx4MoWJdv4KEguBxGX5bJchGkuEHRi55DmnnTRqbNmLRCv72pFY89PXj8_m_5EXJG4YYClbfAJKu0ruWV4dcGgNKq3iMDqlVpU673yeAfOSRHOX8CgAJlBuT8FVcp9rN1DrGL0_UwtsM8cz0O-xQ95hwW0xNy0Lou4-lfPSYfjw_vo-dq_Pb0MrofV55LtawMpa5co0QLEvjEoVHUGdEoIzho3wAqVysnJDDDlHCC8YlqnUKvoQGG_JhcbueW1V8rzEs7D9lj17kFxlW2StSyFtLoQl7sJJmklCrGCyi2oE8x54St7VOYu7S2FOzGnd2IsRsx1nD7687WJXa3jWF59ztgstkHXHhsQkK_tE0Muwf8AAA3c4E</recordid><startdate>1993</startdate><enddate>1993</enddate><creator>Perrett, D.I.</creator><creator>Oram, M.W.</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7QO</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>1993</creationdate><title>Neurophysiology of shape processing</title><author>Perrett, D.I. ; Oram, M.W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c367t-911a01674f0603bae971a94d794308cd0e7a57a46029274a423b7fa7ec80d02e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1993</creationdate><topic>computational modelling</topic><topic>object recognition</topic><topic>pattern processing</topic><topic>single-unit</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Perrett, D.I.</creatorcontrib><creatorcontrib>Oram, M.W.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology Research Abstracts</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Image and vision computing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Perrett, D.I.</au><au>Oram, M.W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Neurophysiology of shape processing</atitle><jtitle>Image and vision computing</jtitle><date>1993</date><risdate>1993</risdate><volume>11</volume><issue>6</issue><spage>317</spage><epage>333</epage><pages>317-333</pages><issn>0262-8856</issn><eissn>1872-8138</eissn><abstract>Recent physiological findings are reviewed and synthesized into a model of shape processing and object recognition. Gestalt laws (e.g. good continuation, closure) and ‘non-accidental’ image properties (e.g. colinear terminating lines) are resolved in prestriate visual cortex, (areas V2 and V3) to support the extraction of 2D shape boundaries. Processing of shape continues along a ventral route through inferior temporal (IT) cortex where a vast catalogue of 2D shape primitives is established. Each catalogue entry is size-specific (±0.5 log scale unit) and orientation-specific (±45°), but can generalize over position (±150 degree
2). Several shape components are used to activate representations of the
approximate
appearance of one object type at one view, orientation and size. Subsequent generalization, first over orientation and size, then over view, and finally over object sub-component, is achieved in the anterior temporal cortex by combining descriptions of the same object from different orientations and views, through associative learning. This scheme provides a route to 3D object recognition through 2D shape description and reduces the problem of perceptual invariance to a series of independent analyses with an associative link established between the outputs. The system relies on parallel processing with computations performed in a series of hierarchical steps with relatively simple operations at each stage.</abstract><pub>Elsevier B.V</pub><doi>10.1016/0262-8856(93)90011-5</doi><tpages>17</tpages></addata></record> |
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title | Neurophysiology of shape processing |
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