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PartLabeling: A Label Management Framework in 3D Space
Elezovikj, Semir Jia, Jianqing Tan, Chiu C. Ling, Haibin
Elezovikj, Semir
Jia, Jianqing
Tan, Chiu C.
Ling, Haibin
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Journal article
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2023-12-22
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Computer and Information Sciences
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https://doi.org/10.1016/j.vrih.2023.06.004
Abstract
In this work, we focus on the label layout problem: specifying the positions of overlaid virtual annotations in Virtual/Augmented Reality scenarios. Designing a layout of labels that does not violate domain-specific design requirements, while at the same time satisfying aesthetic and functional principles of good design, can be a daunting task even for skilled visual designers. Presenting the annotations in 3D object space instead of projection space, allows for the preservation of spatial and depth cues. This results in stable layouts in dynamic environments, since the annotations are anchored in 3D space. In this paper we make two major contributions. First, we propose a technique for managing the layout and rendering of annotations in Virtual/Augmented Reality scenarios by manipulating the annotations directly in 3D space. For this, we make use of Artificial Potential Fields and use 3D geometric constraints to adapt them in 3D space. Second, we introduce PartLabeling: an open source platform in the form of a web application that acts as a much-needed generic framework allowing to easily add labeling algorithms and 3D models. This serves as a catalyst for researchers in this field to make their algorithms and implementations publicly available, as well as ensure research reproducibility. The PartLabeling framework relies on a dataset that we generate as a subset of the original PartNet dataset [17] consisting of models suitable for the label management task. The dataset consists of 1,000 3D models with part annotations.
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Semir Elezovikj, Jianqing Jia, Chiu C. Tan, Haibin Ling, PartLabeling: A Label Management Framework in 3D Space, Virtual Reality & Intelligent Hardware, Volume 5, Issue 6, 2023, Pages 490-508, ISSN 2096-5796, https://doi.org/10.1016/j.vrih.2023.06.004.
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Elsevier
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Virtual Reality & Intelligent Hardware, Vol. 5, Iss. 6
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