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2 March 2022 3D shape modeling based on low-dimension data
Yifan Zhu, Cong Peng
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Proceedings Volume 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021); 1215812 (2022) https://doi.org/10.1117/12.2626855
Event: 2021 International Conference on Computer Vision and Pattern Analysis, 2021, Guangzhou, China
Abstract
3D modeling is a long-standing task in computer vision. However, it is very difficult to directly obtain the complete 3D data. Thus, recovering 3D model from low-dimension information is an important issue. Researchers have developed many methods to solve this problem. This paper presents comprehensive state-of-the-art works on this problem. We firstly introduce the image-driven 3D modeling methods, including single-image-based and multi-image-based ways. Then we summarize the completion-based methods, which is to build a 3D shape from fragmentary observation, such as partial point cloud. Quantitative and qualitative comparisons of the mentioned methods are also presented.
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Yifan Zhu and Cong Peng "3D shape modeling based on low-dimension data", Proc. SPIE 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021), 1215812 (2 March 2022); https://doi.org/10.1117/12.2626855
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KEYWORDS
3D modeling
3D acquisition
3D image processing
Computer aided design
Machine vision
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