Graph approach for Gibson's ecological optics with dynamics of network motifs.
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| Title: | Graph approach for Gibson's ecological optics with dynamics of network motifs. |
|---|---|
| Authors: | Lee, Gi-bbeum1 (AUTHOR), Lee, Ji-Hyun1 (AUTHOR) jihyunlee@kaist.ac.kr |
| Source: | Advanced Engineering Informatics. Jan2026:Part A, Vol. 69, pN.PAG-N.PAG. 1p. |
| Subjects: | Visual perception, Visual optics, Graph theory, Perceptual-motor processes, Entropy (Information theory), Geographic spatial analysis |
| Abstract: | Dynamic visual perception in complex environments is central to understanding the interaction between organisms and their surroundings. Ecological optics depicts that the visual system gains optical information from ambient light, which is structured by relative movements between organism and environment. Recent advances have developed theoretical models of optical information, commonly formalized as optical flows, that account for the perception–action link. However, these frameworks have had limited capacity to inform environmental design, due to a gap between the micro-scale, formalized models of optical information and meso-scale, semantic analyses of observer experience. To address this gap, building on basic principles of ecological optics, we develop a framework that characterizes observers' perception–action patterns by integrating graph-theoretic concepts and measures. Our framework discretizes spatial and temporal trajectories of ambient light experienced by an observer, in the form of a weighted directed graph. This graph approach directly reveals dynamics of perception–action patterns via network motifs—recurring subgraph patterns within a larger graph. Information entropy, as a temporal measure of information content, indicates the distinct modes of the dynamics. As a demonstration, a state analysis shows that several transient states in the motif-based dynamics exhibit good correlations with observers' inclination toward places from survey data, validating its potential for spatial analysis. Overall, the proposed framework paves the way towards real-world applications in optimizing dynamic interactions between observer and environment. [ABSTRACT FROM AUTHOR] |
| Copyright of Advanced Engineering Informatics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 189666668 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Graph approach for Gibson's ecological optics with dynamics of network motifs. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Lee%2C+Gi-bbeum%22">Lee, Gi-bbeum</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lee%2C+Ji-Hyun%22">Lee, Ji-Hyun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jihyunlee@kaist.ac.kr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Advanced+Engineering+Informatics%22">Advanced Engineering Informatics</searchLink>. Jan2026:Part A, Vol. 69, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Visual+perception%22">Visual perception</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+optics%22">Visual optics</searchLink><br /><searchLink fieldCode="DE" term="%22Graph+theory%22">Graph theory</searchLink><br /><searchLink fieldCode="DE" term="%22Perceptual-motor+processes%22">Perceptual-motor processes</searchLink><br /><searchLink fieldCode="DE" term="%22Entropy+%28Information+theory%29%22">Entropy (Information theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Geographic+spatial+analysis%22">Geographic spatial analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Dynamic visual perception in complex environments is central to understanding the interaction between organisms and their surroundings. Ecological optics depicts that the visual system gains optical information from ambient light, which is structured by relative movements between organism and environment. Recent advances have developed theoretical models of optical information, commonly formalized as optical flows, that account for the perception–action link. However, these frameworks have had limited capacity to inform environmental design, due to a gap between the micro-scale, formalized models of optical information and meso-scale, semantic analyses of observer experience. To address this gap, building on basic principles of ecological optics, we develop a framework that characterizes observers' perception–action patterns by integrating graph-theoretic concepts and measures. Our framework discretizes spatial and temporal trajectories of ambient light experienced by an observer, in the form of a weighted directed graph. This graph approach directly reveals dynamics of perception–action patterns via network motifs—recurring subgraph patterns within a larger graph. Information entropy, as a temporal measure of information content, indicates the distinct modes of the dynamics. As a demonstration, a state analysis shows that several transient states in the motif-based dynamics exhibit good correlations with observers' inclination toward places from survey data, validating its potential for spatial analysis. Overall, the proposed framework paves the way towards real-world applications in optimizing dynamic interactions between observer and environment. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Advanced Engineering Informatics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.aei.2025.103865 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Visual perception Type: general – SubjectFull: Visual optics Type: general – SubjectFull: Graph theory Type: general – SubjectFull: Perceptual-motor processes Type: general – SubjectFull: Entropy (Information theory) Type: general – SubjectFull: Geographic spatial analysis Type: general Titles: – TitleFull: Graph approach for Gibson's ecological optics with dynamics of network motifs. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Lee, Gi-bbeum – PersonEntity: Name: NameFull: Lee, Ji-Hyun IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2026:Part A Type: published Y: 2026 Identifiers: – Type: issn-print Value: 14740346 Numbering: – Type: volume Value: 69 Titles: – TitleFull: Advanced Engineering Informatics Type: main |
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