4-D Spatiotemporal Detection and Modeling of Free-Bending Pipelines in Cluttered 3-D Point Cloud

Zhang, Jie; Sun, Junhua

doi:10.1109/tim.2021.3115209

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Cited by 7 publications

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“…Patil et al 6 propose an area‐based adaptive Hough transform to detect peaks in parameter space and estimate the orientation of the pipeline. Zhang and Sun 7 detect pipelines through 4D spatiotemporal representations. Cheng et al 8 propose a deep learning‐based 3D pipeline modeling algorithm.…”

Section: Related Workmentioning

confidence: 99%

Real‐time reconstruction of pipes using RGB‐D cameras

Kim,

Ahn,

Kim

et al. 2023

Computer Animation & Virtual

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This paper presents a novel method that automatically reconstructs pipes in real time using an RGB‐D camera. The input image is decomposed into superpixels, and a pipe element, which is a 3D circle lying on the pipe surface, is generated for each superpixel. Over frames, the pipe elements are grouped into sequences and are finally modeled in parametric equations. The method is tested in daily settings, where the pipes may be curved and their radii may vary along the axes. The test results show that the method is able to reconstruct pipes efficiently, precisely and robustly.

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Section: Related Workmentioning

confidence: 99%