3D Shape Estimation for Smooth Surfaces Using Double Mirror System

2021 ◽  
Vol 2021 (18) ◽  
pp. 69-1-69-11
Author(s):  
Yin Wang ◽  
Davi He ◽  
Zillion Lin ◽  
George Chiu ◽  
Jan Allebach
Keyword(s):  
3D Reconstruction ◽  
Camera Calibration ◽  
Low Cost ◽  
Depth Map ◽  
Mirror System ◽  
Reconstruction Method ◽  
Single Camera ◽  
Shape Estimation ◽  
Calibration Process ◽  
3D Shape

In this paper, a low cost, single camera, double mirror system that can be built in a desktop nail printer will be described. The usage of this system is to capture an image of a fingernail and to generate the 3D shape of the nail. The nail’s depth map will be estimated from this rendered 3D nail shape. The paper will describe the camera calibration process and explain the calibration theory for this proposed system. Then a 3D reconstruction method will be introduced, as well. Experimental results will be shown in the paper, which illustrate the accuracy of the system to handle the rendering task.

scholarly journals A Study of 3D Digitisation Modalities for Crime Scene Investigation

2021 ◽  
Vol 1 (2) ◽  
pp. 56-85
Author(s):  
George Galanakis ◽  
Xenophon Zabulis ◽  
Theodore Evdaimon ◽  
Sven-Eric Fikenscher ◽  
Sebastian Allertseder ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Low Cost ◽  
Crime Scene ◽  
Reconstruction Method ◽  
Crime Scene Investigation ◽  
The Public ◽  
Wide Range ◽  
Time Availability ◽  
Scene Investigation ◽  
3D Digitisation

A valuable aspect during crime scene investigation is the digital documentation of the scene. Traditional means of documentation include photography and in situ measurements from experts for further analysis. Although 3D reconstruction of pertinent scenes has already been explored as a complementary tool in investigation pipelines, such technology is considered unfamiliar and not yet widely adopted. This is explained by the expensive and specialised digitisation equipment that is available so far. However, the emergence of high-precision but low-cost devices capable of scanning scenes or objects in 3D has been proven as a reliable alternative to their counterparts. This paper summarises and analyses the state-of-the-art technologies in scene documentation using 3D digitisation and assesses the usefulness in typical police-related situations and the forensics domain in general. We present the methodology for acquiring data for 3D reconstruction of various types of scenes. Emphasis is placed on the applicability of each technique in a wide range of situations, ranging in type and size. The application of each reconstruction method is considered in this context and compared with respect to additional constraints, such as time availability and simplicity of operation of the corresponding scanning modality. To further support our findings, we release a multi-modal dataset obtained from a hypothetical indoor crime scene to the public.

scholarly journals Automated 3D Scenes Reconstruction Using Multiple Stereo Pairs from Portable Four-Camera Photographic Measurement System

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Qi Peng ◽  
Lifen Tu ◽  
Kaibing Zhang ◽  
Sidong Zhong
Keyword(s):  
3D Reconstruction ◽  
Measurement System ◽  
3D Model ◽  
Low Cost ◽  
Reconstruction Method ◽  
Feature Points ◽  
Point Matching ◽  
Mogao Grottoes ◽  
Feature Point Matching ◽  
3D Scene

An effective automatic 3D reconstruction method using a portable four-camera photographic measurement system (PFCPMS) is proposed. By taking advantage of the complementary stereo information from four cameras, a fast and highly accurate feature point matching algorithm is developed for 3D reconstruction. Specifically, we first utilize a projection method to obtain a large number of dense feature points. And then a reduction and clustering treatment is applied to simplify the Delaunay triangulation process and reconstruct a 3D model for each scene. In addition, a 3D model stitching approach is proposed to further improve the performance of the limited field-of-view for image-based method. The experimental results tested on the 172 cave in Mogao Grottoes indicate that the proposed method is effective to reconstruct a 3D scene with a low-cost four-camera photographic measurement system.

scholarly journals 3D Reconstruction Method of Rapeseed Plants in the Whole Growth Period Using RGB-D Camera

2021 ◽  
Author(s):  
Xiaowen Teng ◽  
Guangsheng Zhou ◽  
Yuxuan Wu ◽  
Chenglong Huang ◽  
Wanjing Dong ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Point Cloud ◽  
Near Infrared ◽  
Infrared Image ◽  
Depth Map ◽  
Point Clouds ◽  
Scanning System ◽  
Reconstruction Method ◽  
Hardware Cost ◽  
Scan Time

The 3D reconstruction method using RGB-D camera has a good balance in hardware cost, point cloud quality and automation. However, due to the limitation of inherent structure and imaging principle, the acquired point cloud has problems such as a lot of noise and difficult registration. This paper proposes a three-dimensional reconstruction method using Azure Kinect to solve these inherent problems. Shoot color map, depth map and near-infrared image of the target from six perspectives by Azure Kinect sensor. Multiply the 8-bit infrared image binarization with the general RGB-D image alignment result provided by Microsoft to remove ghost images and most of the background noise. In order to filter the floating point and outlier noise of the point cloud, a neighborhood maximum filtering method is proposed to filter out the abrupt points in the depth map. The floating points in the point cloud are removed before generating the point cloud, and then using the through filter filters out outlier noise. Aiming at the shortcomings of the classic ICP algorithm, an improved method is proposed. By continuously reducing the size of the down-sampling grid and the distance threshold between the corresponding points, the point clouds of each view are continuously registered three times, until get the complete color point cloud. A large number of experimental results on rape plants show that the point cloud accuracy obtained by this method is 0.739mm, a complete scan time is 338.4 seconds, and the color reduction is high. Compared with a laser scanner, the proposed method has considerable reconstruction accuracy and a significantly ahead of the reconstruction speed, but the hardware cost is much lower and it is easy to automate the scanning system. This research shows a low-cost, high-precision 3D reconstruction technology, which has the potential to be widely used for non-destructive measurement of crop phenotype.

3D Reconstruction Based on Single Defocused Microscopic Image

2012 ◽  
Author(s):  
Z. G. Xing ◽  
C. M. Zhao ◽  
J. Wei ◽  
Z. Wei
Keyword(s):  
3D Reconstruction ◽  
High Speed ◽  
Measurement Accuracy ◽  
Low Cost ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Microscopic Image ◽  
Depth Of Focus ◽  
Fuzzy Degree

Microscope has being limited by the depth of focus, while the focused image is clear, the defocused images are fuzzy and fuzzy degree of the object images vary with different defocused distances. This paper presented a 3D reconstruction method based on a defocused microscopic image. After the defocused microscopic image is divided the microscopic into M × N regions, the fuzzy degree of each region is quantitatively evaluated. A corresponding curve of the relation between fuzzy degree and defocus distance is drawn by the presented algorithm in this paper, and then the three-dimensional characteristics of objects are reconstructed. This method has the merits of little computation, low cost and high speed. And M and N values can be changed according to the needs of the measurement accuracy.

scholarly journals PI-Plat: a high-resolution image-based 3D reconstruction method to estimate growth dynamics of rice inflorescence traits

Plant Methods ◽  
2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Jaspreet Sandhu ◽  
Feiyu Zhu ◽  
Puneet Paul ◽  
Tian Gao ◽  
Balpreet K. Dhatt ◽  
...  
Keyword(s):  
High Resolution ◽  
3D Reconstruction ◽  
Low Cost ◽  
Crop Improvement ◽  
Growth Dynamics ◽  
Superior Performance ◽  
Plant Phenotyping ◽  
Reconstruction Method ◽  
Color Intensity ◽  
Non Destructive

Abstract Background Recent advances in image-based plant phenotyping have improved our capability to study vegetative stage growth dynamics. However, more complex agronomic traits such as inflorescence architecture (IA), which predominantly contributes to grain crop yield are more challenging to quantify and hence are relatively less explored. Previous efforts to estimate inflorescence-related traits using image-based phenotyping have been limited to destructive end-point measurements. Development of non-destructive inflorescence phenotyping platforms could accelerate the discovery of the phenotypic variation with respect to inflorescence dynamics and mapping of the underlying genes regulating critical yield components. Results The major objective of this study is to evaluate post-fertilization development and growth dynamics of inflorescence at high spatial and temporal resolution in rice. For this, we developed the Panicle Imaging Platform (PI-Plat) to comprehend multi-dimensional features of IA in a non-destructive manner. We used 11 rice genotypes to capture multi-view images of primary panicle on weekly basis after the fertilization. These images were used to reconstruct a 3D point cloud of the panicle, which enabled us to extract digital traits such as voxel count and color intensity. We found that the voxel count of developing panicles is positively correlated with seed number and weight at maturity. The voxel count from developing panicles projected overall volumes that increased during the grain filling phase, wherein quantification of color intensity estimated the rate of panicle maturation. Our 3D based phenotyping solution showed superior performance compared to conventional 2D based approaches. Conclusions For harnessing the potential of the existing genetic resources, we need a comprehensive understanding of the genotype-to-phenotype relationship. Relatively low-cost sequencing platforms have facilitated high-throughput genotyping, while phenotyping, especially for complex traits, has posed major challenges for crop improvement. PI-Plat offers a low cost and high-resolution platform to phenotype inflorescence-related traits using 3D reconstruction-based approach. Further, the non-destructive nature of the platform facilitates analyses of the same panicle at multiple developmental time points, which can be utilized to explore the genetic variation for dynamic inflorescence traits in cereals.

scholarly journals PI-Plat: A high-resolution image-based 3D reconstruction method to estimate growth dynamics of rice inflorescence traits

2019 ◽  
Author(s):  
Jaspreet Sandhu ◽  
Feiyu Zhu ◽  
Puneet Paul ◽  
Tian Gao ◽  
Balpreet K. Dhatt ◽  
...  
Keyword(s):  
High Resolution ◽  
3D Reconstruction ◽  
Low Cost ◽  
Crop Improvement ◽  
Growth Dynamics ◽  
Superior Performance ◽  
Plant Phenotyping ◽  
Reconstruction Method ◽  
Color Intensity ◽  
Non Destructive

AbstractBackgroundRecent advances in image-based plant phenotyping have improved our capability to study vegetative stage growth dynamics. However, more complex agronomic traits such as inflorescence architecture (IA), which predominantly contributes to grain crop yield are more challenging to quantify and hence are relatively less explored. Previous efforts to estimate inflorescence-related traits using image-based phenotyping have been limited to destructive end-point measurements. Development of non-destructive inflorescence phenotyping platforms could accelerate the discovery of the phenotypic variation with respect to inflorescence dynamics and mapping of the underlying genes regulating critical yield components.ResultsThe major objective of this study is to evaluate post-fertilization development and growth dynamics of inflorescence at high spatial and temporal resolution in rice. For this, we developed the Panicle Imaging Platform (PI-Plat) to comprehend multi-dimensional features of IA in a non-destructive manner. We used 11 rice genotypes to capture multi-view images of primary panicle on weekly basis after the fertilization. These images were used to reconstruct a 3D point cloud of the panicle, which enabled us to extract digital traits such as voxel count and color intensity. We found that the voxel count of developing panicles is positively correlated with seed number and weight at maturity. The voxel count from developing panicles projected overall volumes that increased during the grain filling phase, wherein quantification of color intensity estimated the rate of panicle maturation. Our 3D based phenotyping solution showed superior performance compared to conventional 2D based approaches.ConclusionsFor harnessing the potential of the existing genetic resources, we need a comprehensive understanding of the genotype-to-phenotype relationship. Relatively low-cost sequencing platforms have facilitated high-throughput genotyping, while phenotyping, especially for complex traits, has posed major challenges for crop improvement. PI-Plat offers a low cost and high-resolution platform to phenotype inflorescence-related traits using 3D reconstruction-based approach. Further, the non-destructive nature of the platform facilitates analyses of the same panicle at multiple developmental time points, which can be utilized to explore the genetic variation for dynamic inflorescence traits in cereals.

scholarly journals Monocular 3D reconstruction of sail flying shape using passive markers

2021 ◽  
Vol 32 (1) ◽  
Author(s):  
Luiz Maciel ◽  
Ricardo Marroquim ◽  
Marcelo Vieira ◽  
Kevyn Ribeiro ◽  
Alexandre Alho
Keyword(s):  
3D Reconstruction ◽  
Low Cost ◽  
Bundle Adjustment ◽  
Single Camera ◽  
Naval Architecture ◽  
Domain Experts ◽  
Simulation Results

AbstractWe present a method to recover the 3D flying shape of a sail using passive markers. In the navigation and naval architecture domain, retrieving the sail shape may be of immense value to confirm or contest simulation results, and to aid the design of new optimal sails. Our acquisition setup is very simple and low-cost, as it is only necessary to fix a series of printable markers on the sail and register the flying shape in real sailing conditions from a side vessel with a single camera. We reconstruct the average sail shape during an interval where the sailor maintains the sail as stable as possible. The average is further improved by a Bundle Adjustment algorithm. We tested our method in a real sailing scenario and present promising results. Quantitatively, we show the precision in regards to the reconstructed markers area and the reprojected points. Qualitatively, we present feedback from domain experts who evaluated our results and confirmed the usefulness and quality of the reconstructed shape.

Sign in / Sign up

Export Citation Format

Share Document