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Observation-driven generation of texture maps depicting dust accumulation over time
The perception of realism in computer-generated images can be significantly enhanced by subtle visual cues. Among those, one can highlight the presence of dust on synthetic objects, which is often subject to temporal variations in real settings. In this paper, we present a framework for the generati...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10110734/ https://www.ncbi.nlm.nih.gov/pubmed/37091062 http://dx.doi.org/10.1007/s00371-022-02457-7 |
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author | Santos, Rebecca L C Baranoski, Gladimir V G |
author_facet | Santos, Rebecca L C Baranoski, Gladimir V G |
author_sort | Santos, Rebecca L C |
collection | PubMed |
description | The perception of realism in computer-generated images can be significantly enhanced by subtle visual cues. Among those, one can highlight the presence of dust on synthetic objects, which is often subject to temporal variations in real settings. In this paper, we present a framework for the generation of textures representing the accumulation of this ubiquitous material over time in indoor settings. It employs a physically inspired approach to portray the effects of different levels of accumulated dust roughness on the appearance of substrate surfaces and to modulate these effects according to the different illumination and viewing geometries. The development of its core algorithms was guided by empirical insights and data obtained from observational experiments which are also described. To illustrate its applicability to the rendering of visually plausible depictions of time-dependent changes in dusty scenes, we provide sequences of images obtained considering distinct dust accumulation scenarios. |
format | Online Article Text |
id | pubmed-10110734 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-101107342023-04-19 Observation-driven generation of texture maps depicting dust accumulation over time Santos, Rebecca L C Baranoski, Gladimir V G Vis Comput Original Article The perception of realism in computer-generated images can be significantly enhanced by subtle visual cues. Among those, one can highlight the presence of dust on synthetic objects, which is often subject to temporal variations in real settings. In this paper, we present a framework for the generation of textures representing the accumulation of this ubiquitous material over time in indoor settings. It employs a physically inspired approach to portray the effects of different levels of accumulated dust roughness on the appearance of substrate surfaces and to modulate these effects according to the different illumination and viewing geometries. The development of its core algorithms was guided by empirical insights and data obtained from observational experiments which are also described. To illustrate its applicability to the rendering of visually plausible depictions of time-dependent changes in dusty scenes, we provide sequences of images obtained considering distinct dust accumulation scenarios. Springer Berlin Heidelberg 2022-04-02 2023 /pmc/articles/PMC10110734/ /pubmed/37091062 http://dx.doi.org/10.1007/s00371-022-02457-7 Text en © The Author(s) 2022, corrected publication 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | Original Article Santos, Rebecca L C Baranoski, Gladimir V G Observation-driven generation of texture maps depicting dust accumulation over time |
title | Observation-driven generation of texture maps depicting dust accumulation over time |
title_full | Observation-driven generation of texture maps depicting dust accumulation over time |
title_fullStr | Observation-driven generation of texture maps depicting dust accumulation over time |
title_full_unstemmed | Observation-driven generation of texture maps depicting dust accumulation over time |
title_short | Observation-driven generation of texture maps depicting dust accumulation over time |
title_sort | observation-driven generation of texture maps depicting dust accumulation over time |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10110734/ https://www.ncbi.nlm.nih.gov/pubmed/37091062 http://dx.doi.org/10.1007/s00371-022-02457-7 |
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