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Journal Article
UTexGen: High Quality Texture Reconstruction for Large-Scale Scenes Using Multi-View Images
- Authors
- Hye-Sun Kim, Yun-Ji Ban, Chang-Joon Park
- Issue Date
- 2024-12
- Citation
- ETRI Journal, v.권호미정, pp.1-13
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원
- Language
- English
- Type
- Journal Article
- Abstract
- When reconstructing extensive terrain, it is essential to partition it into smaller tiles for individual processing. This paper introduces a texture reconstruction approach that ensures seamless and consistent final outputs, even when processed tile by tile. Among the stages of multi-view image-based reconstruction, texture reconstruction presents significant challenges during tile-based processing. Relying solely on local tile-level data complicates achieving precise texture mapping. The absence of occlusion details between tiles can lead to selecting incorrect images as the best visible ones or adjusting tile texture colors differently, resulting in noticeable grid-like texture seams in the final result. To mitigate these issues, we leverage global depth maps to accurately detect occlusions between neighboring tiles. Furthermore, by utilizing a shared texture candidate list, we establish uniform targets for texture color correction across tiles. Experimental findings demonstrate that leveraging global information for texture reconstruction on a tile-by-tile basis enables the creation of smooth and realistic texture maps, as validated through comparisons with existing methodologies.
- KSP Keywords
- Color correction, Depth Map, Image-based reconstruction, global information, large-scale, multi-view images, texture mapping, texture reconstruction
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
