Three-dimensional(3D)parametric measurements of individual gravels in the Gobi region using point cloud technique

Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gravels.The proposed workflow yields accurate calculations of relevant parameters for Gobi gravels,providing essential data support for subsequent studies on Gobi environments.

SAR regional all-azimuth observation orbit design for target 3D reconstruction

Three-dimensional(3D) synthetic aperture radar(SAR)extends the conventional 2D images into 3D features by several acquisitions in different aspects. Compared with 3D techniques via multiple observations in elevation, e.g. SAR interferometry(InSAR) and SAR tomography(TomoSAR), holographic SAR can retrieve 3D structure by observations in azimuth. This paper focuses on designing a novel type of orbit to achieve SAR regional all-azimuth observation(AAO) for embedded targets detection and holographic 3D reconstruction. The ground tracks of the AAO orbit separate the earth surface into grids. Target in these grids can be accessed with an azimuth angle span of360°, which is similar to the flight path of airborne circular SAR(CSAR). Inspired from the successive coverage orbits of optical sensors, several optimizations are made in the proposed method to ensure favorable grazing angles, the performance of 3D reconstruction, and long-term supervision for SAR sensors. Simulation experiments show the regional AAO can be completed within five hours. In addition, a second AAO of the same area can be duplicated in two days. Finally, an airborne SAR data process result is presented to illustrate the significance of AAO in 3D reconstruction.

3D Echocardiogram Reconstruction Employing a Flip Directional Texture Pyramid

Three dimensional(3D)echocardiogram enables cardiologists to visua-lize suspicious cardiac structures in detail.In recent years,this three-dimensional echocardiogram carries important clinical value in virtual surgical simulation.However,this 3D echocardiogram involves a trade-off difficulty between accu-racy and efficient computation in clinical diagnosis.This paper presents a novel Flip Directional 3D Volume Reconstruction(FD-3DVR)method for the recon-struction of echocardiogram images.The proposed method consists of two main steps:multiplanar volumetric imaging and 3D volume reconstruction.In the crea-tion of multiplanar volumetric imaging,two-dimensional(2D)image pixels are mapped into voxels of the volumetric grid.As the obtained slices are discontin-uous,there are some missing voxels in the volume data.To restore the structural and textural information of 3D ultrasound volume,the proposed method creates a volume pyramid in parallel with theflip directional texture pyramid.Initially,the nearest neighbors of missing voxels in the multiplanar volumetric imaging are identified by 3D ANN(Approximate Nearest Neighbor)patch matching method.Furthermore,aflip directional texture pyramid is proposed and aggregated with distance in patch matching tofind out the most similar neighbors.In the recon-struction step,structural and textural information obtained from differentflip angle directions can reconstruct 3D volume well with the desired accuracy.Com-pared with existing 3D reconstruction methods,the proposed Flip Directional 3D Volume Reconstruction(FD-3DVR)method provides superior performance for the mean peak signal-to-noise ratio(40.538 for the proposed method I and 39.626 for the proposed method II).Experimental results performed on the cardi-ac datasets demonstrate the efficiency of the proposed method for the reconstruc-tion of echocardiogram images.

Three-Dimensional Model Reconstruction of Nonwovens from Multi-Focus Images

The three-dimensional(3D)model is of great significance to analyze the performance of nonwovens.However,the existing modelling methods could not reconstruct the 3D structure of nonwovens at low cost.A new method based on deep learning was proposed to reconstruct 3D models of nonwovens from multi-focus images.A convolutional neural network was trained to extract clear fibers from sequence images.Image processing algorithms were used to obtain the radius,the central axis,and depth information of fibers from the extraction results.Based on this information,3D models were built in 3D space.Furthermore,self-developed algorithms optimized the central axis and depth of fibers,which made fibers more realistic and continuous.The method with lower cost could reconstruct 3D models of nonwovens conveniently.

3D Vector Reconstruction of the Typical Cervical Vertebra from Anatomical Sections of Korean Visible Human at the Laboratory of Clinical and Digital Anatomy of Paris Descartes University

Aim: To carry out a 3D vector reconstruction of the typical cervical vertebra from anatomical sections of the “Korean Visible Human” for educational purposes. Material and Methods: The anatomical subject was a 33-year-old Korean man who died of leukemia. He was 164 cm tall and weighed 55 kg. This man donated his body to science. Her body was frozen and cut into several anatomical sections after an MRI and CT scan. These anatomical sections were made using a special saw called a 0.2 mm thick cryomacrotome. Thus 8100 cuts were obtained. Only the sections numbered 940 to 1200 were used for our study. A segmentation by manual contouring of the different parts of the typical cervical vertebra was made using the software Winsurf version 3.5 on a laptop PC running Windows 7 equipped with a Ram of 8 gigas. Results: Our 3D vector model of the typical cervical vertebra is easily manipulated using the Acrobat 3DPDF interface. Each part of the vertebra accessible in a menu can be displayed, hidden or made transparent, and 3D labels are available as well as educational menus for learning anatomy. Conclusion: This original work constitutes a remarkable educational tool for the anatomical study of the typical cervical vertebra and can also be used as a 3D atlas for simulation purposes for training in therapeutic gestures.

Visual perception driven 3D building structure representa tion from airborne laser scanning point cloud

Background Three-dimensional(3D)building models with unambiguous roof plane geometry parameters,roof structure units,and linked topology provide essential data for many applications related to human activities in urban environments.The task of 3D reconstruction from point clouds is still in the development phase,especially the recognition and interpretation of roof topological structures.Methods This study proposes a novel visual perception-based approach to automatically decompose and reconstruct building point clouds into meaningful and simple parametric structures,while the associated mutual relationships between the roof plane geometry and roof structure units are expressed by a hierarchical topology tree.First,a roof plane extraction is performed by a multi-label graph cut energy optimization framework and a roof structure graph(RSG)model is then constructed to describe the roof topological geometry with common adjacency,symmetry,and convexity rules.Moreover,a progressive roof decomposition and refinement are performed,generating a hierarchical representation of the 3D roof structure models.Finally,a visual plane fitted residual or area constraint process is adopted to generate the RSG model with different levels of details.Results Two airborne laser scanning datasets with different point densities and roof styles were tested,and the performance evaluation metrics were obtained by International Society for Photogrammetry and Remote Sensing,achieving a correctness and accuracy of 97.7%and 0.29m,respectively.Conclusions The standardized assessment results demonstrate the effectiveness and robustness of the proposed approach,showing its ability to generate a variety of structural models,even with missing data.

Research on CT characteristics reconstruction technology

The traditional computed tomography(CT)reconstruction methods are noisy,low resolution,poor contrast,and generally not suitable to detect the smaller flaws.Besides,the filter design is also difficult.The CT characteristics reconstruction technology was brought forward to improve in these aspects,which is defined to directly reconstruct the characteristics of the projection for the best requirements not the overall image quality.The two-dimension(2D)and three-dimension(3D)CT characteristics reconstruction algorithm were firstly introduced,then by detailed analysis,experimental results and comparsion of parameters calculated,its advantages in keeping better high-frequency feature,better noise immunity,short time-consuming and easier design are verified.

Characterization of 3D pore nanostructure and stress-dependent permeability of organic-rich shales in northern Guizhou Depression,China

The three-dimensional(3D)pore structures and permeability of shale are critical for forecasting gas production capacity and guiding pressure differential control in practical reservoir extraction.However,few investigations have analyzed the effects of microscopic organic matter(OM)morphology and 3D pore nanostructures on the stress sensitivity,which are precisely the most unique and controlling factors of reservoir quality in shales.In this study,ultra-high nanoscale-resolution imaging experiments,i.e.focused ion beam-scanning electron microscopy(FIB-SEMs),were conducted on two organic-rich shale samples from Longmaxi and Wufeng Formations in northern Guizhou Depression,China.Pore morphology,porosity of 3D pore nanostructures,pore size distribution,and connectivity of the six selected regions of interest(including clump-shaped OMs,interstitial OMs,framboidal pyrite,and microfractures)were qualitatively and quantitatively characterized.Pulse decay permeability(PDP)measurement was used to investigate the variation patterns of stress-dependent permeability and stress sensitivity of shales under different confining pressures and pore pressures,and the results were then used to calculate the Biot coefficients for the two shale formations.The results showed that the samples have high OM porosity and 85%of the OM pores have the radius of less than 40 nm.The OM morphology and pore structure characteristics of the Longmaxi and Wufeng Formations were distinctly different.In particular,the OM in the Wufeng Formation samples developed some OM pores with radius larger than500 nm,which significantly improved the connectivity.The macroscopic permeability strongly depends on the permeability of OM pores.The stress sensitivity of permeability of Wufeng Formation was significantly lower than that of Longmaxi Formation,due to the differences in OM morphology and pore structures.The Biot coefficients of 0.729 and 0.697 were obtained for the Longmaxi and Wufeng Formations,respectively.

Detecting repetitive structures on building footprints for the purposes of 3D modeling and reconstruction

Repetitive structures of a building share features in terms of geometries and appearance and,therefore,the 3D information for these structures can be transferred from one specification to another for the purpose of 3D modeling and reconstruction once they are identified as repetitive structures.In this paper,a novel approach is proposed for the detection of the repetitive structures specified by the polygons of a building’s footprints.Instead of directly operating on the polygon in 2D space,the polygon is converted into a bend angle function representation in 1D space,whereby an extrusion is represented as a closed polygon intersected by the x-axis and located above it,while an intrusion is represented as a closed polygon below the x-axis.In this way,a polygon of a footprint is decomposed into a number of extrusions and intrusions which can in turn be processed.The task of detecting any repetitive structures specified in a building’s footprints then becomes the task of clustering the intersected polygons in the bend angle function space.The extrusions/intrusions which can be placed in the same clusters can be regarded as repetitive structures.Experiments show that this proposed approach can detect repetitive structures with different sizes,orientations and complexities.

机载激光雷达3维建筑物模型重建的研究进展

机载激光雷达系统已经成为3维建筑物模型快速重建的重要手段。综述了国内外利用机载激光雷达点云进行3维建筑物模型重建的研究方法、进展情况,分析讨论了模型驱动法、数据驱动法和混合法的特点及关键问题。混合法集成了模型驱动方法和数据驱动方法的优点,是该项技术今后发展的重点领域。

Deep3DSketch-im:rapid high-fidelity AI 3D model generation by single freehand sketches

The rise of artificial intelligence generated content(AIGC)has been remarkable in the language and image fields,but artificial intelligence(AI)generated three-dimensional(3D)models are still under-explored due to their complex nature and lack of training data.The conventional approach of creating 3D content through computer-aided design(CAD)is labor-intensive and requires expertise,making it challenging for novice users.To address this issue,we propose a sketch-based 3D modeling approach,Deep3DSketch-im,which uses a single freehand sketch for modeling.This is a challenging task due to the sparsity and ambiguity.Deep3DSketch-im uses a novel data representation called the signed distance field(SDF)to improve the sketch-to-3D model process by incorporating an implicit continuous field instead of voxel or points,and a specially designed neural network that can capture point and local features.Extensive experiments are conducted to demonstrate the effectiveness of the approach,achieving state-of-the-art(SOTA)performance on both synthetic and real datasets.Additionally,users show more satisfaction with results generated by Deep3DSketch-im,as reported in a user study.We believe that Deep3DSketch-im has the potential to revolutionize the process of 3D modeling by providing an intuitive and easy-to-use solution for novice users.

基于LIDAR数据的建筑物提取和三维重建的研究进展

本文阐述了基于LIDAR数据提取建筑物以及对其三维重建的一般过程,着重介绍LIDAR数据中建筑物信息提取的有关算法以及进行三维重建的可行性方法。

A fast, accurate and dense feature matching algorithm for aerial images

Three-dimensional(3D)reconstruction based on aerial images has broad prospects,and feature matching is an important step of it.However,for high-resolution aerial images,there are usually problems such as long time,mismatching and sparse feature pairs using traditional algorithms.Therefore,an algorithm is proposed to realize fast,accurate and dense feature matching.The algorithm consists of four steps.Firstly,we achieve a balance between the feature matching time and the number of matching pairs by appropriately reducing the image resolution.Secondly,to realize further screening of the mismatches,a feature screening algorithm based on similarity judgment or local optimization is proposed.Thirdly,to make the algorithm more widely applicable,we combine the results of different algorithms to get dense results.Finally,all matching feature pairs in the low-resolution images are restored to the original images.Comparisons between the original algorithms and our algorithm show that the proposed algorithm can effectively reduce the matching time,screen out the mismatches,and improve the number of matches.

单幅高分辨率SAR图像建筑物三维模型重构

提出了一种利用高分辨率SAR图像进行建筑物提取和三维重构的方法.首先,分析了高分辨率SAR图像建筑物产生的电磁散射的类型,给出了不同类型散射区域的后向散射计算方法,并在此基础上给出了一种利用建筑物三维CAD模型进行SAR建筑物特征区域图像仿真的方法;其次,给出了利用建筑物的二次散射结构确定建筑物底部轮廓位置和方向的方法,并提出了一种基于分布密度函数差异的仿真图像迭代匹配方法,进行建筑物高度的反演.仿真SAR图像后向散射系数用来划分建筑物不同的散射区域,通过计算特征区域之间的分布密度函数差异,以取得最大匹配度值的仿真图像对应的检验高度作为建筑物的反演高度;最后,选用了两幅不同屋顶类型的实际机载高分辨率SAR图像进行建筑物提取和三维重构实验,试验结果较为理想,验证了所提方法的可行性和有效性.

有限元法在动物组织模型构建上的应用进展

有限元法是指通过对医学组织图像(CT)的三维重建,将其转换为具有直观立体效果的三维有限元模型,通过对有限元模型进行材料选取、施加载荷、求解等操作,得到有限元组织模型的力学特性,从而更清楚的观察组织的应力、应变过程。该技术可以更好地处理复杂的生物力学问题而被广泛应用于生物医学领域,目前把有限元法和动物组织结合起来的研究逐渐成为了热点。论文对有限元法在动物组织模型构建上的研究前景和应用优势进行综述,为动物组织模型构建方面的研究提供新的方法和思路。

面向单体建筑精细化建模的无人机三维航线规划

文章提出了一种面向单体建筑精细化建模的无人机三维航线规划方案。该方案使用测绘无人机与单个相机作为单体建筑三维建模信息获取的平台,基于传统航空摄影测量技术,结合近景摄影测量方法,将无人机飞行摄影航线改进为三维环绕式,提高建筑物侧面特征点的提取精度,有效地解决了快速获取单体建筑三维精细化建模所需要的信息这一问题。

High-resolution electron microscopy for heterogeneous catalysis research

Heterogeneous catalysts are the most important catalysts in industrial reactions. Nanocatalysts, with size ranging from hundreds of nanometers to the atomic scale, possess activities that are closely connected to their structural characteristics such as particle size, surface morphology, and three-dimensional topography. Recently, the development of advanced analytical transmission electron microscopy（TEM） techniques, especially quantitative high-angle annular darkfield（HAADF） imaging and high-energy resolution spectroscopy analysis in scanning transmission electron microscopy（STEM） at the atomic scale, strengthens the power of（S）TEM in analyzing the structural/chemical information of heterogeneous catalysts. Three-dimensional reconstruction from two-dimensional projected images and the real-time recording of structural evolution during catalytic reactions using in-situ（S）TEM methods further broaden the scope of（S）TEM observation. The atomic-scale structural information obtained from high-resolution（S）TEM has proven to be of significance for better understanding and designing of new catalysts with enhanced performance.

Radial Hahn Moment Invariants for 2D and 3D Image Recognition

Recently, orthogonal moments have become efficient tools for two-dimensional and three-dimensional（2D and 3D） image not only in pattern recognition, image vision, but also in image processing and applications engineering. Yet, there is still a major difficulty in 3D rotation invariants. In this paper, we propose new sets of invariants for 2D and 3D rotation, scaling and translation based on orthogonal radial Hahn moments. We also present theoretical mathematics to derive them. Thus, this paper introduces in the first case new 2D radial Hahn moments based on polar representation of an object by one-dimensional orthogonal discrete Hahn polynomials, and a circular function. In the second case, we present new 3D radial Hahn moments using a spherical representation of volumetric image by one-dimensional orthogonal discrete Hahn polynomials and a spherical function. Further 2D and 3D invariants are derived from the proposed 2D and 3D radial Hahn moments respectively, which appear as the third case. In order to test the proposed approach, we have resolved three issues： the image reconstruction, the invariance of rotation, scaling and translation, and the pattern recognition. The result of experiments show that the Hahn moments have done better than the Krawtchouk moments, with and without noise. Simultaneously, the mentioned reconstruction converges quickly to the original image using 2D and 3D radial Hahn moments, and the test images are clearly recognized from a set of images that are available in COIL-20 database for 2D image, and Princeton shape benchmark（PSB） database for 3D image.

Automatic Outer Surface Extraction of Femoral Head in CT Images

Computer-aided hip surgery planning and implant design applications require accurate segmentation of femoral head and proximal acetabulum. An accurate outer surface extraction of femoral head using marching cubes algorithm remains challenging due to deformed shapes and extremely narrow inter-bone regions. In this paper, we present an automatic and fast approach for segmentation of femoral head and proximal acetabulum which leads to accurate and compact representation of femoral head using marching cubes algorithm. At first, valley-emphasized images are constructed from original images so that valleys stand out in high relief. Otsu's multiple thresholding technique is applied to seperate the images into bone and non-bone classes. Region growing method and threedimensional(3D) morphological operations are performed to fill holes in the bone. In the reclassification process,the bone regions are further segmented, and the boundaries of the bone regions are further refined based on Bayes decision rule. Finally, marching cubes algorithm is applied to reconstruct a 3D model and extract the outer surface of femoral head and proximal acetabulum. Experimental results show that this method is an accurate segmentation technique for femoral head and proximal acetabulum and it can be applied as a tool in medical practice.

顾及地形的城市三维可视化方法研究

介绍了三维房屋重建与城市可视化方法研究和应用模块开发的初步成果。在一般二维不规则三角网的基础上，发展了有确定边界条件下的二维不规则三角网，通过对顾及地形的铅直墙面和不规则屋顶的分别构网和合成，形成建筑物的表面不规则三角网，消去共面条件下的公共边后，实现了顾及地形的的城市房屋重建。