Landmark Recognition using Deep Learning in a Virtual Space

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dc.contributor.authorMukai, Nobuhikoen_US
dc.contributor.authorUematsu, Takashien_US
dc.contributor.authorChang, Younghaen_US
dc.contributor.editorAbey Campbellen_US
dc.contributor.editorClaudia Krogmeieren_US
dc.contributor.editorGareth Youngen_US
dc.date.accessioned2023-12-04T15:44:57Z
dc.date.available2023-12-04T15:44:57Z
dc.date.issued2023
dc.description.abstractIt is a very important issue to simulate human behavior in a virtual space for emergency evacuation in the real world. Humans take actions using their own eyes and memory. Then, the identification of the scene that virtual humans are looking at in a town is one of the key elements of the behavior, and image-based pattern matching is usually used; however, the accuracy is affected by the view angle and the length between the target object and the position at which the image is taken. This paper proposes a method to identify the images of landmarks that are placed at the corners in an intersection in a virtual space using a deep learning method and reports the relationship between the accuracy and the area rate that the landmark object occupies in the image.en_US
dc.description.sectionheadersPosters and Demos
dc.description.seriesinformationICAT-EGVE 2023 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments - Posters and Demos
dc.identifier.doi10.2312/egve.20231343
dc.identifier.isbn978-3-03868-236-3
dc.identifier.issn1727-530X
dc.identifier.pages33-34
dc.identifier.pages2 pages
dc.identifier.urihttps://doi.org/10.2312/egve.20231343
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egve20231343
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies -> Instance-based learning
dc.subjectComputing methodologies
dc.subjectInstance
dc.subjectbased learning
dc.titleLandmark Recognition using Deep Learning in a Virtual Spaceen_US
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