{"title":"A seed point placement method for generating streamlines in context regions","authors":"Qian Zhang, Zeyao Mo, HuaWei Wang, Li Xiao","doi":"10.1007/s12650-024-01019-4","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Streamline is one of the main methods for flow field visualization, which describes the distribution pattern of the flow field through the flow trajectory of seed points. Currently, most of the work focuses on seed point placement and streamline generation in feature regions. For context regions (blank areas), i.e., context regions without features, however, there is little research conducted. In fact, the context regions carry some flow field information, which can assist researcher in deeply understanding the entire spatial distribution of the flow field as well as the continuous transition between different feature regions. However, it is a challenging problem to generate suitable streamlines in context regions. If the streamlines are not positioned properly or have a too large number, they may severely occlude the feature regions, while too few streamlines may be difficult to fill in the entire information of the flow field. To address the problem, this article proposes a new method for seed point placement that mainly focuses on context regions. The method is divided into two steps: finding context regions and then placing seed points in context regions. Firstly, use 3D to 2D projection transformation and region connectivity algorithm to find context regions, where no feature streamlines pass through. The streamlines in a context region often have similar directions due to being away from critical points. Then, according to the direction of the streamlines, evenly place seed points in the 3D space. As a result, spatially uniform streamlines are generated to fill the context regions, which makes the flow field information more complete. Qualitative and quantitative evaluations show that the method proposed in this article can generate visually uniform streamlines in context regions, together with feature streamlines, which can help researchers to coherently understand the overall characteristics of the flow field.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>","PeriodicalId":54756,"journal":{"name":"Journal of Visualization","volume":"1412 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Visualization","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s12650-024-01019-4","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Streamline is one of the main methods for flow field visualization, which describes the distribution pattern of the flow field through the flow trajectory of seed points. Currently, most of the work focuses on seed point placement and streamline generation in feature regions. For context regions (blank areas), i.e., context regions without features, however, there is little research conducted. In fact, the context regions carry some flow field information, which can assist researcher in deeply understanding the entire spatial distribution of the flow field as well as the continuous transition between different feature regions. However, it is a challenging problem to generate suitable streamlines in context regions. If the streamlines are not positioned properly or have a too large number, they may severely occlude the feature regions, while too few streamlines may be difficult to fill in the entire information of the flow field. To address the problem, this article proposes a new method for seed point placement that mainly focuses on context regions. The method is divided into two steps: finding context regions and then placing seed points in context regions. Firstly, use 3D to 2D projection transformation and region connectivity algorithm to find context regions, where no feature streamlines pass through. The streamlines in a context region often have similar directions due to being away from critical points. Then, according to the direction of the streamlines, evenly place seed points in the 3D space. As a result, spatially uniform streamlines are generated to fill the context regions, which makes the flow field information more complete. Qualitative and quantitative evaluations show that the method proposed in this article can generate visually uniform streamlines in context regions, together with feature streamlines, which can help researchers to coherently understand the overall characteristics of the flow field.
Journal of VisualizationCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
CiteScore
3.40
自引率
5.90%
发文量
79
审稿时长
>12 weeks
期刊介绍：
Visualization is an interdisciplinary imaging science devoted to making the invisible visible through the techniques of experimental visualization and computer-aided visualization.
The scope of the Journal is to provide a place to exchange information on the latest visualization technology and its application by the presentation of latest papers of both researchers and technicians.
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