SEEVis: A Smart Emergency Evacuation Plan Visualization System with Data-Driven Shot Designs

dc.contributor.authorLi, Quanen_US
dc.contributor.authorLiu, Yingjie J.en_US
dc.contributor.authorChen, Lien_US
dc.contributor.authorYang, Xingchao C.en_US
dc.contributor.authorPeng, Yien_US
dc.contributor.authorYuan, Xiaoru R.en_US
dc.contributor.authorWijerathne, Maddegedara Lalith Lakshmanen_US
dc.contributor.editorViola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatianaen_US
dc.date.accessioned2020-05-24T13:01:50Z
dc.date.available2020-05-24T13:01:50Z
dc.date.issued2020
dc.description.abstractDespite the significance of tracking human mobility dynamics in a large-scale earthquake evacuation for an effective first response and disaster relief, the general understanding of evacuation behaviors remains limited. Numerous individual movement trajectories, disaster damages of civil engineering, associated heterogeneous data attributes, as well as complex urban environment all obscure disaster evacuation analysis. Although visualization methods have demonstrated promising performance in emergency evacuation analysis, they cannot effectively identify and deliver the major features like speed or density, as well as the resulting evacuation events like congestion or turn-back. In this study, we propose a shot design approach to generate customized and narrative animations to track different evacuation features with different exploration purposes of users. Particularly, an intuitive scene feature graph that identifies the most dominating evacuation events is first constructed based on user-specific regions or their tracking purposes on a certain feature. An optimal camera route, i.e., a storyboard is then calculated based on the previous user-specific regions or features. For different evacuation events along this route, we employ the corresponding shot design to reveal the underlying feature evolution and its correlation with the environment. Several case studies confirm the efficacy of our system. The feedback from experts and users with different backgrounds suggests that our approach indeed helps them better embrace a comprehensive understanding of the earthquake evacuation.en_US
dc.description.number3
dc.description.sectionheadersVisual Analytics for Problem Solving
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.13999
dc.identifier.issn1467-8659
dc.identifier.pages523-535
dc.identifier.urihttps://doi.org/10.1111/cgf.13999
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13999
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.subjectHuman centered computing
dc.subjectVisualization
dc.subjectVisualization design and evaluation methods
dc.titleSEEVis: A Smart Emergency Evacuation Plan Visualization System with Data-Driven Shot Designsen_US
Files
Original bundle
Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
v39i3pp523-535.pdf
Size:
8.03 MB
Format:
Adobe Portable Document Format
No Thumbnail Available
Name:
1046-file1.mp4
Size:
119.55 MB
Format:
Unknown data format
Collections