Near-optimal combination of disparity across a log-polar scaled visual field.
The human visual system is foveated: we can see fine spatial details in central vision, whereas resolution is poor in our peripheral visual field, and this loss of resolution follows an approximately logarithmic decrease. Additionally, our brain organizes visual input in polar coordinates. Therefore...
| Váldodahkkit: | , , , |
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| Materiálatiipa: | Artihkal |
| Giella: | English |
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Public Library of Science (PLoS)
2020-04-01
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| Ráidu: | PLoS Computational Biology |
| Liŋkkat: | https://doi.org/10.1371/journal.pcbi.1007699 |
| _version_ | 1830177392419667968 |
|---|---|
| author | Guido Maiello Manuela Chessa Peter J Bex Fabio Solari |
| author_facet | Guido Maiello Manuela Chessa Peter J Bex Fabio Solari |
| author_sort | Guido Maiello |
| collection | DOAJ |
| description | The human visual system is foveated: we can see fine spatial details in central vision, whereas resolution is poor in our peripheral visual field, and this loss of resolution follows an approximately logarithmic decrease. Additionally, our brain organizes visual input in polar coordinates. Therefore, the image projection occurring between retina and primary visual cortex can be mathematically described by the log-polar transform. Here, we test and model how this space-variant visual processing affects how we process binocular disparity, a key component of human depth perception. We observe that the fovea preferentially processes disparities at fine spatial scales, whereas the visual periphery is tuned for coarse spatial scales, in line with the naturally occurring distributions of depths and disparities in the real-world. We further show that the visual system integrates disparity information across the visual field, in a near-optimal fashion. We develop a foveated, log-polar model that mimics the processing of depth information in primary visual cortex and that can process disparity directly in the cortical domain representation. This model takes real images as input and recreates the observed topography of human disparity sensitivity. Our findings support the notion that our foveated, binocular visual system has been moulded by the statistics of our visual environment. |
| first_indexed | 2024-12-17T19:24:41Z |
| format | Article |
| id | doaj.art-8c8a8253534c4575be16e0c4d0123ece |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-17T19:24:41Z |
| publishDate | 2020-04-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-8c8a8253534c4575be16e0c4d0123ece2022-12-21T21:35:25ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582020-04-01164e100769910.1371/journal.pcbi.1007699Near-optimal combination of disparity across a log-polar scaled visual field.Guido MaielloManuela ChessaPeter J BexFabio SolariThe human visual system is foveated: we can see fine spatial details in central vision, whereas resolution is poor in our peripheral visual field, and this loss of resolution follows an approximately logarithmic decrease. Additionally, our brain organizes visual input in polar coordinates. Therefore, the image projection occurring between retina and primary visual cortex can be mathematically described by the log-polar transform. Here, we test and model how this space-variant visual processing affects how we process binocular disparity, a key component of human depth perception. We observe that the fovea preferentially processes disparities at fine spatial scales, whereas the visual periphery is tuned for coarse spatial scales, in line with the naturally occurring distributions of depths and disparities in the real-world. We further show that the visual system integrates disparity information across the visual field, in a near-optimal fashion. We develop a foveated, log-polar model that mimics the processing of depth information in primary visual cortex and that can process disparity directly in the cortical domain representation. This model takes real images as input and recreates the observed topography of human disparity sensitivity. Our findings support the notion that our foveated, binocular visual system has been moulded by the statistics of our visual environment.https://doi.org/10.1371/journal.pcbi.1007699 |
| spellingShingle | Guido Maiello Manuela Chessa Peter J Bex Fabio Solari Near-optimal combination of disparity across a log-polar scaled visual field. PLoS Computational Biology |
| title | Near-optimal combination of disparity across a log-polar scaled visual field. |
| title_full | Near-optimal combination of disparity across a log-polar scaled visual field. |
| title_fullStr | Near-optimal combination of disparity across a log-polar scaled visual field. |
| title_full_unstemmed | Near-optimal combination of disparity across a log-polar scaled visual field. |
| title_short | Near-optimal combination of disparity across a log-polar scaled visual field. |
| title_sort | near optimal combination of disparity across a log polar scaled visual field |
| url | https://doi.org/10.1371/journal.pcbi.1007699 |
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