scholarly journals 3D RECONSTRUCTION-REVERSE ENGINEERING – DIGITAL FABRICATION OF THE EGYPTIAN PALERMO STONE USING BY SMARTPHONE AND LIGHT STRUCTURED SCANNER

2018 ◽  
Vol XLII-2 ◽  
pp. 311-318 ◽  
Author(s):  
F. Di Paola ◽  
L. Inzerillo
Keyword(s):  
3D Reconstruction ◽  
Reverse Engineering ◽  
3D Model ◽  
Structured Light ◽  
Digital Fabrication ◽  
Black Stone ◽  
Structured Light Scanner ◽  
Dark Colour ◽  
Egyptian History ◽  
Texture Reconstruction

This paper presents a pipeline that has been developed to acquire a shape with particular features both under the geometric and radiometric aspects. In fact, the challenge was to build a 3D model of the black Stone of Palermo, where the oldest Egyptian history was printed with the use of hieroglyphs. The dark colour of the material and the superficiality of the hieroglyphs' groove have made the acquisition process very complex to the point of having to experiment with a pipeline that allows the structured light scanner not to lose the homologous points in the 3D alignment phase. For the texture reconstruction we used a last generation smartphone.

scholarly journals DENSE 3D OBJECT RECONSTRUCTION USING STRUCTURED-LIGHT SCANNER AND DEEP LEARNING

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 777-783
Author(s):  
V. V. Kniaz ◽  
V. A. Mizginov ◽  
L. V. Grodzitkiy ◽  
N. A. Fomin ◽  
V. A. Knyaz
Keyword(s):  
Optical Flow ◽  
3D Model ◽  
Stereo Matching ◽  
Structured Light ◽  
Primary Source ◽  
Ground Truth ◽  
Complex Surface ◽  
Systems Model ◽  
Structured Light Scanner ◽  
Starting Point

Abstract. Structured light scanners are intensively exploited in various applications such as non-destructive quality control at an assembly line, optical metrology, and cultural heritage documentation. While more than 20 companies develop commercially available structured light scanners, structured light technology accuracy has limitations for fast systems. Model surface discrepancies often present if the texture of the object has severe changes in brightness or reflective properties of its texture. The primary source of such discrepancies is errors in the stereo matching caused by complex surface texture. These errors result in ridge-like structures on the surface of the reconstructed 3D model. This paper is focused on the development of a deep neural network LineMatchGAN for error reduction in 3D models produced by a structured light scanner. We use the pix2pix model as a starting point for our research. The aim of our LineMatchGAN is a refinement of the rough optical flow A and generation of an error-free optical flow B̂. We collected a dataset (which we term ZebraScan) consisting of 500 samples to train our LineMatchGAN model. Each sample includes image sequences (Sl, Sr), ground-truth optical flow B and a ground-truth 3D model. We evaluate our LineMatchGAN on a test split of our ZebraScan dataset that includes 50 samples. The evaluation proves that our LineMatchGAN improves the stereo matching accuracy (optical flow end point error, EPE) from 0.05 pixels to 0.01 pixels.

scholarly journals Application of Computer Modeling for Planning Plastic Surgeries

2014 ◽  
Vol 5 (4) ◽  
pp. 18-25
Author(s):  
Klaudia Jamrozik ◽  
Jakub Rusek ◽  
Dominik Szozda ◽  
Krzysztof Karbowski
Keyword(s):  
Reverse Engineering ◽  
Plastic Surgery ◽  
Computer Modeling ◽  
Structured Light ◽  
Visualization Method ◽  
Engineering Technology ◽  
Structured Light Scanner ◽  
Surgery First

Abstract The paper presents the application results of reverse engineering technology for planning the plastic surgery. First step is digitalization of the patient body. It is realized by 3D structured light scanner. The scanning data are transferred into 3dsMax software and used for planning plastic surgery. The planning effect is shown using stereoscopy visualization method.

Bioengineering Applications of 3D Scanning and Reconstruction Using a Depth Sensor

2015 ◽  
Vol 809-810 ◽  
pp. 920-925 ◽  
Author(s):  
Octavian Ciobanu
Keyword(s):  
3D Reconstruction ◽  
Real Time ◽  
3D Model ◽  
Low Cost ◽  
Structured Light ◽  
3D Scanning ◽  
Kinect Sensor ◽  
Depth Sensor ◽  
3D Surfaces

Paper approaches some characteristics and bioengineering applications of a handheld depth sensor for low-cost 3D scanning and reconstruction. The Kinect depth sensor used in this work was launched on June 2009 and was based around a gaming webcam peripheral. The Kinect sensor uses a structured light technique in order to develop real-time 3D surfaces. The 3D model of anatomic surface may have a lot of bioengineering applications. Some observations and comparisons are presented in connection with the scanning and 3D reconstruction of different anatomic surfaces.

scholarly journals 3D Reconstruction with Single-Shot Structured Light RGB Line Pattern

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4819
Author(s):  
Yikang Li ◽  
Zhenzhou Wang
Keyword(s):  
3D Reconstruction ◽  
Moving Objects ◽  
Structured Light ◽  
Color Space ◽  
Reconstruction Technique ◽  
Single Shot ◽  
Line Pattern ◽  
Hsv Color Space ◽  
Phase Map ◽  
Line Segmentation

Single-shot 3D reconstruction technique is very important for measuring moving and deforming objects. After many decades of study, a great number of interesting single-shot techniques have been proposed, yet the problem remains open. In this paper, a new approach is proposed to reconstruct deforming and moving objects with the structured light RGB line pattern. The structured light RGB line pattern is coded using parallel red, green, and blue lines with equal intervals to facilitate line segmentation and line indexing. A slope difference distribution (SDD)-based image segmentation method is proposed to segment the lines robustly in the HSV color space. A method of exclusion is proposed to index the red lines, the green lines, and the blue lines respectively and robustly. The indexed lines in different colors are fused to obtain a phase map for 3D depth calculation. The quantitative accuracies of measuring a calibration grid and a ball achieved by the proposed approach are 0.46 and 0.24 mm, respectively, which are significantly lower than those achieved by the compared state-of-the-art single-shot techniques.

3D reconstruction and simulation for raceway groove of bearings based on structured light

2006 ◽  
Author(s):  
Qinghua Wu ◽  
Wei Li ◽  
Wenjun Wu ◽  
Ming Zhong ◽  
Tao He ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Structured Light

Virtual skeletons: using a structured light scanner to create a 3D faunal comparative collection

2009 ◽  
Vol 36 (9) ◽  
pp. 2018-2023 ◽  
Author(s):  
Laura Niven ◽  
Teresa E. Steele ◽  
Hannes Finke ◽  
Tim Gernat ◽  
Jean-Jacques Hublin
Keyword(s):  
Structured Light ◽  
Structured Light Scanner

scholarly journals Ray calibration and phase mapping for structured-light-field 3D reconstruction

2018 ◽  
Vol 26 (6) ◽  
pp. 7598 ◽  
Author(s):  
Zewei Cai ◽  
Xiaoli Liu ◽  
Xiang Peng ◽  
Bruce Z. Gao
Keyword(s):  
3D Reconstruction ◽  
Light Field ◽  
Structured Light ◽  
Phase Mapping
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