ArticleSensors (Basel, Switzerland)2019
High-Accuracy Globally Consistent Surface Reconstruction Using Fringe Projection Profilometry.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 18 citations in OpenAlex.
- An Improved Projector Calibration Method by Phase Mapping Based on Fringe Projection Profilometry.Sensors (Basel, Switzerland) · 2023Article
- A Combined Measurement Method for Large-Size Aerospace Components.Sensors (Basel, Switzerland) · 2020Article
- Single-Shot Structured Light Sensor for 3D Dense and Dynamic Reconstruction.Sensors (Basel, Switzerland) · 2020Article
- Special Issue on Visual Sensors.Sensors (Basel, Switzerland) · 2020Article
- Adaptive Binocular Fringe Dynamic Projection Method for High Dynamic Range Measurement.Sensors (Basel, Switzerland) · 2019Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
This paper presents a high-accuracy method for globally consistent surface reconstruction using a single fringe projection profilometry (FPP) sensor. To solve the accumulated sensor pose estimation error problem encountered in a long scanning trajectory, we first present a novel 3D registration method which fuses both dense geometric and curvature consistency constraints to improve the accuracy of relative sensor pose estimation. Then we perform global sensor pose optimization by modeling the surface consistency information as a pre-computed covariance matrix and formulating the multi-view point cloud registration problem in a pose graph optimization framework. Experiments on reconstructing a 1300 mm × 400 mm workpiece with a FPP sensor is performed, verifying that our method can substantially reduce the accumulated error and achieve industrial-level surface model reconstruction without any external positional assistance but only using a single FPP sensor.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.