Point normal orientation and surface reconstruction by incorporating isovalue constraints to Poisson equation

Xiao, Dong; Shi, Zuoqiang; Li, Siyu; Deng, Bailin; Wang, Bin

doi:10.1016/j.cagd.2023.102195

Cited by 11 publications

(2 citation statements)

References 39 publications

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“…IsoPoisson by Xiao et al. [XSL*23] incorporate an isovalue constraint to the Poisson equation, which helps with consistent normal orientation and consequently improved reconstruction.…”

Section: Related Workmentioning

confidence: 99%

PPSurf: Combining Patches and Point Convolutions for Detailed Surface Reconstruction

Erler,

Fuentes‐Perez,

Hermosilla

et al. 2024

Computer Graphics Forum

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Abstract3D surface reconstruction from point clouds is a key step in areas such as content creation, archaeology, digital cultural heritage and engineering. Current approaches either try to optimize a non‐data‐driven surface representation to fit the points, or learn a data‐driven prior over the distribution of commonly occurring surfaces and how they correlate with potentially noisy point clouds. Data‐driven methods enable robust handling of noise and typically either focus on a global or a local prior, which trade‐off between robustness to noise on the global end and surface detail preservation on the local end. We propose PPSurf as a method that combines a global prior based on point convolutions and a local prior based on processing local point cloud patches. We show that this approach is robust to noise while recovering surface details more accurately than the current state‐of‐the‐art. Our source code, pre‐trained model and dataset are available at https://github.com/cg‐tuwien/ppsurf.

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“…IsoPoisson by Xiao et al. [XSL*23] incorporate an isovalue constraint to the Poisson equation, which helps with consistent normal orientation and consequently improved reconstruction.…”

Section: Related Workmentioning

confidence: 99%

PPSurf: Combining Patches and Point Convolutions for Detailed Surface Reconstruction

Erler,

Fuentes‐Perez,

Hermosilla

et al. 2024

Computer Graphics Forum

View full text Add to dashboard Cite

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“…Surface reconstruction [18] is a vital task in the form characterization of freeform surfaces [19], and some robust surface fitting and reconstruction algorithms have been studied, like bidirectional sampling method [20], handling cross-sections method [21], interpolating scattered 3D surface [22], and etc. With the rapid development in computer graphics [23], reverse engineering from point clouds [24] is gradually applied in various fields.…”

Section: Introductionmentioning

confidence: 99%

A smooth surface measurement method by flexible contact using multiple fingers device

Gong,

Li,

Wang

et al. 2024

Meas. Sci. Technol.

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Contact measurement technology is commonly used for analysis and modeling of three-dimensional (3D) object. This paper presents a contact measurement method, using a claw type probe based on a set of rotary encoders that can flexibly contact objects with efficiently multi-lines scanning. In this paper, a 3D measurement system by flexible contact of multiple fingers was built. The claw probe was set on a coordinate measurement machine. By moving the position of the claw for interpolation detection to improve the sampling rate, higher precision 3D reconstruction was achieved. Also, a compensation algorithm was proposed for this type detector to improve measuring accuracy. In the experiments, two surface models were produced by 3D printing as the test objects. By comparing the designed surface with the reconstructed surface, it is demonstrated that this system can effectively and softly measure smooth surface, like the back of human body, which is valuable for further study and use in rehabilitation massage, apparel design, and etc.

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A computer-vision based framework for virtual 3D garment reconstruction

Dang,

Ruan Wan,

et al. 2024

Multimed Tools Appl

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Existing 3D garment reconstruction methods are difficult to implement for online fashion design and e-commerce or special applications. This paper proposes a novel computer-vision framework for 3D garment digital reconstruction, which aims to reconstruct high-quality and realistic virtual 3D garments with fabric mechanic properties for 3D virtual try-on. The new segmentation scheme is proposed to separate the 3D garment point clouds from background points, which is suitable for 3D human shapes and is adaptive for different 3D garment models in different scenes. The new Statistical Outlier Removal algorithm and the learning-based method PointCleanNet are combined to remove noise and outliers in 3D garment point clouds, which provides high-fidelity and high-quality 3D garment point clouds. The 3D garment meshes are then reconstructed from their corresponding point clouds with a modified rolling ball algorithm. Finally, the meshes are improved and converted into physics-based virtual try-on 3D garments with fabric mechanic properties added, which enables the assessment of different body shapes with varied sizes for the same reconstructed 3D garment. Comparison experiments demonstrate that our framework achieves high-quality and realistic 3D garment reconstruction and accurate 3D virtual try-on from 2D garment images. We also demonstrate the proposed framework on a large range of various garments to show this approach has a great potential for garment future technology, such as online garment shopping, garment design and manufacturing.

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Point normal orientation and surface reconstruction by incorporating isovalue constraints to Poisson equation

Cited by 11 publications

References 39 publications

PPSurf: Combining Patches and Point Convolutions for Detailed Surface Reconstruction

PPSurf: Combining Patches and Point Convolutions for Detailed Surface Reconstruction

A smooth surface measurement method by flexible contact using multiple fingers device

A computer-vision based framework for virtual 3D garment reconstruction

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