Psychophysical measurement of perceived motion flow of naturalistic scenes
© 2023 The Author(s)..
The neural and computational mechanisms underlying visual motion perception have been extensively investigated over several decades, but little attempt has been made to measure and analyze, how human observers perceive the map of motion vectors, or optical flow, in complex naturalistic scenes. Here, we developed a psychophysical method to assess human-perceived motion flows using local vector matching and a flash probe. The estimated perceived flow for naturalistic movies agreed with the physically correct flow (ground truth) at many points, but also showed consistent deviations from the ground truth (flow illusions) at other points. Comparisons with the predictions of various computational models, including cutting-edge computer vision algorithms and coordinate transformation models, indicated that some flow illusions are attributable to lower-level factors such as spatiotemporal pooling and signal loss, while others reflect higher-level computations, including vector decomposition. Our study demonstrates a promising data-driven psychophysical paradigm for an advanced understanding of visual motion perception.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:26 |
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| Enthalten in: |
iScience - 26(2023), 12 vom: 15. Dez., Seite 108307 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Yang, Yung-Hao [VerfasserIn] |
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| Links: |
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| Themen: |
Applied computing |
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| Anmerkungen: |
Date Revised 01.12.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1016/j.isci.2023.108307 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a The neural and computational mechanisms underlying visual motion perception have been extensively investigated over several decades, but little attempt has been made to measure and analyze, how human observers perceive the map of motion vectors, or optical flow, in complex naturalistic scenes. Here, we developed a psychophysical method to assess human-perceived motion flows using local vector matching and a flash probe. The estimated perceived flow for naturalistic movies agreed with the physically correct flow (ground truth) at many points, but also showed consistent deviations from the ground truth (flow illusions) at other points. Comparisons with the predictions of various computational models, including cutting-edge computer vision algorithms and coordinate transformation models, indicated that some flow illusions are attributable to lower-level factors such as spatiotemporal pooling and signal loss, while others reflect higher-level computations, including vector decomposition. Our study demonstrates a promising data-driven psychophysical paradigm for an advanced understanding of visual motion perception | ||
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