Interactive Texture Segmentation of 3D Scanned Models Leveraging Multiview Automatic Segmentation

In 3D model scanning, the raw texture of a 3D model often requires segmentation into distinct regions to apply different material properties to each region. Current methods, such as manual segmentation, are labor-intensive, while automatic segmentation techniques lack user control. We propose an interactive tool that combines automatic segmentation with minimal manual intervention, striking an optimal balance between efficiency and control. Following a multiview automatic segmentation process that divides the texture into small subsegments, users cluster the subsegments into segments by drawing simple scribbles in the 3D model view. We show that our approach results in more detailed subsegments compared to automatic segmentation approaches. Furthermore, a user study confirms that our approach improves segmentation accuracy and quality compared to manual segmentation with standard 3D computer graphics software. This research paves the way to more efficient texture segmentation in 3D model scanning.

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Publication Details

Journal
IEEE Computer Graphics and Applications
Published
2025-01-01
DOI
https://doi.org/10.1109/mcg.2025.3595378
Citations
1
Primary Topic
3D Shape Modeling and Analysis
Type
article
Field-Weighted Citation Impact
1.33
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article

Interactive Texture Segmentation of 3D Scanned Models Leveraging Multiview Automatic Segmentation

Tsukasa Takagi, Taisuke Hashimoto, Fabrice Matulic, Koki Madono et al.
1 citations
IEEE Computer Graphics and Applications
3D Shape Modeling and Analysis
1.33
article

Interactive Texture Segmentation of 3D Scanned Models Leveraging Multiview Automatic Segmentation

Tsukasa Takagi, Taisuke Hashimoto, Fabrice Matulic, Koki Madono, Keita Higuchi, Takeo Igarashi, Hiroharu Kato
article en
1 citations

Abstract

In 3D model scanning, the raw texture of a 3D model often requires segmentation into distinct regions to apply different material properties to each region. Current methods, such as manual segmentation, are labor-intensive, while automatic segmentation techniques lack user control. We propose an interactive tool that combines automatic segmentation with minimal manual intervention, striking an optimal balance between efficiency and control. Following a multiview automatic segmentation process that divides the texture into small subsegments, users cluster the subsegments into segments by drawing simple scribbles in the 3D model view. We show that our approach results in more detailed subsegments compared to automatic segmentation approaches. Furthermore, a user study confirms that our approach improves segmentation accuracy and quality compared to manual segmentation with standard 3D computer graphics software. This research paves the way to more efficient texture segmentation in 3D model scanning.

IEEE Computer Graphics and ApplicationsVol. PP
Waseda University (JP), Preferred Networks (Japan) (JP)
Openalex Percentile: Top 20%
3D Shape Modeling and Analysis
1.33
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Interactive Texture Segmentation of 3D Scanned Models Leveraging Multiview Automatic Segmentation — Tsukasa Takagi, Taisuke Hashimoto, et al. · IEEE Computer Graphics and Applications (2025) | TGRS Research Map | TGRS