Large-scale spatial data visualization method based on augmented reality

Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.

RWNeRF:Robust Watermarking Scheme for Neural Radiance Fields Based on Invertible Neural Networks

As neural radiance fields continue to advance in 3D content representation,the copyright issues surrounding 3D models oriented towards implicit representation become increasingly pressing.In response to this challenge,this paper treats the embedding and extraction of neural radiance field watermarks as inverse problems of image transformations and proposes a scheme for protecting neural radiance field copyrights using invertible neural network watermarking.Leveraging 2D image watermarking technology for 3D scene protection,the scheme embeds watermarks within the training images of neural radiance fields through the forward process in invertible neural networks and extracts them from images rendered by neural radiance fields through the reverse process,thereby ensuring copyright protection for both the neural radiance fields and associated 3D scenes.However,challenges such as information loss during rendering processes and deliberate tampering necessitate the design of an image quality enhancement module to increase the scheme’s robustness.This module restores distorted images through neural network processing before watermark extraction.Additionally,embedding watermarks in each training image enables watermark information extraction from multiple viewpoints.Our proposed watermarking method achieves a PSNR(Peak Signal-to-Noise Ratio)value exceeding 37 dB for images containing watermarks and 22 dB for recovered watermarked images,as evaluated on the Lego,Hotdog,and Chair datasets,respectively.These results demonstrate the efficacy of our scheme in enhancing copyright protection.

A Study of Precision Factors of Large-scale Object Surface Profile Laser Scanning Measurement

In this paper, we presented a method of using the l as er scanning triangulation for the non-contact 3D surface profile measurement of large-scale object. The characteristic of large-scale object non-contact mea surement is analyzed and the measuring method is proposed. Main factors influenc ing measurement precision such as image distortion and accurate designation of s peckle center are analyzed and methods of solving these problems are proposed. W e designed a combined filter by which the pulse noise and the Gaussian noise of speckle image can be eliminated efficiently. Using the characteristic of intensi ty distribution of laser speckle image we proposed a new approximating method th at could locate the center of laser speckle image at sub-pixel. The auxiliary v ariables are set to linearize the relationship between the image displacement an d the distance, the accurate values of laser triangulation system parameters cou ld be calibrated accurately and the measuring precision is increased remarkabl y. Using the above techniques we designed a measuring system based on laser sc anning triangulation. The results of the experiment show that these methods can raise the measuring precision of large-scale 3D surface profile effectively.

3D scene graph prediction from point clouds

Background In this study,we propose a novel 3D scene graph prediction approach for scene understanding from point clouds.Methods It can automatically organize the entities of a scene in a graph,where objects are nodes and their relationships are modeled as edges.More specifically,we employ the DGCNN to capture the features of objects and their relationships in the scene.A Graph Attention Network(GAT)is introduced to exploit latent features obtained from the initial estimation to further refine the object arrangement in the graph structure.A one loss function modified from cross entropy with a variable weight is proposed to solve the multi-category problem in the prediction of object and predicate.Results Experiments reveal that the proposed approach performs favorably against the state-of-the-art methods in terms of predicate classification and relationship prediction and achieves comparable performance on object classification prediction.Conclusions The 3D scene graph prediction approach can form an abstract description of the scene space from point clouds.

汽车驾驶模拟器中3D场景的设计和实现

1 引言汽车驾驶模拟器是一种能正确模拟汽车驾驶操作,并能在主要性能上获得与实车相同感觉的汽车驾驶训练仿真教学设备。一个好的模拟器应该有一个立体感强、图形逼真的三维视景。YF三维汽车驾驶模拟器的视景系统采用计算机实时生成技术(称为CIG视景系统),它根据当前汽车的状态实时生成逼真的三维场景,使学员感觉就象驾驶真的汽车一样。

一种改进了的AABB算法在3D场景少儿益智系统中的应用

碰撞检测是三维系统中实现系统角色真实感物理运动的主要算法。通过对碰撞检测AABB算法深入研究,针对碰撞检测AABB算法的运算量大、紧密性差的问题,利用BSP树剖分法和相交叉检测算法对其做了改进。并将其应用于3D场景少儿益智系统中,经实验分析,改进的碰撞检测算法能有效地减少了系统运算次数,提高了系统的运行速度。

From 2D to 3D GIS for CyberCity

In order to understand the 3D landscape with many h igh buildings in a city, the 2D GIS has to be extended to 3D GIS. The further de velopment of CyberCity has to include various applications of 3D scenes from the outdoor scenes to the indoor ones. In thispaper, some key techniques, such as data management method and dynamicalvisualization method for the outdoor and the indoor scenes, are discussed.The indoor scene is compared with the outdoor one. The idea of integratedrepresentation of the outdoor and the indoor scenes in CyberCity GIS is discusse d.

虚拟现实与3D动画应用于犯罪现场重建之初探

测绘、摄影是记录意外事故和犯罪现场的主要方式,碍于传统技术只能呈现或输出平面的2D影像,与真实的3D环境相较,往往可能丢失关键的证据信息,如何弥补此一缺憾,是鉴识科学亟待解决的问题。通过建立3D犯罪现场之技术,改善传统2D犯罪现场纪录的缺点,快速建立的3D模型,搭配3D动画应用鉴识动画的模拟技术,可套用于特定犯罪类型,来描绘犯罪的细节。涉及案情特征描述的3D动画,不仅运用于重大刑案的侦查与重建,也已开始在法庭上使用。除回顾虚拟现实实验室在他国警政信息化之建置与真实应用,还通过3D计算机技术的实作呈现,为中国犯罪现场重建开辟另一曙光;希望将新科技运用在法庭上,以科学的方式证明嫌犯是否无辜,提供法官决策之重要依据,对于中国刑案现场教学经验亦能有所裨益。

基于X3D/VRML构建金沙地区古场景

虚拟现实技术已广泛应用于考古领域,为文物和古环境的再现提供了平台。X3D作为VMRL语言的继承版本,是新的3D图形规范。本文以X3D/VRML为工具,结合现有的虚拟现实技术对三维虚拟古场景的开发原理和技术进行了研究。综合各方面专家的研究成果与文物考古成果,以精确的地理位置再现金沙地区三维古场景,并运用X3D的消息映射机制以及Java对VRML的控制实现了交互功能。基于X3D制作的虚拟现实场景文件体积小,方便网上传输;其平台无关性,便于实现交互功能。

基于AutoCAD和3DSMAX的虚拟校园三维场景构建研究

当前的虚拟校园三维场景构建方法是利用osgEarth获取GoogleEarth数据,构建虚拟校园三维地图,然后依据本地地形信息与三维场景模型完成对虚拟校园的三维场景构建;该方法在三维场景构建过程中没有考虑到校园后续建设发展,只凭现在所需进行三维场景构建,导致虚拟校园三维场景杂乱,存在虚拟校园三维场景构建顾虑不周的问题;为此,提出一种基于AutoCAD和3DSMAX的虚拟校园三维场景构建方法;该方法首先利用Kinect的RGB深度摄像头获取校园平面数据、影像数据和贴图资料,采用相机阵列合成算法对所得校园图像进行特征提取,然后依据非局部均值滤波方法对获取的校园图像进行去噪操作,最后利用边缘方向和梯度表示中的结构方向与强度,对校园图像外轮廓的纹理特征进行收敛,依据外轮廓纹理特征收敛实现校园图像内轮廓的准确定位,将校园图像与虚拟校园三维场景构建所需图像进行匹配,由此完成对虚拟校园三维场景的构建;实验结果证明,所提方法是虚拟校园三维场景构建领域革命性的突破,提高了学校的招生率,增加了校园文化历史的展现机会,为该领域的研究发展提供了有效依据。

Multi-source data-based 3D digital preservation of large scale ancient chinese architecture:A case report

The 3D digitalization and documentation of ancient Chinese architecture is challenging because of architectural complexity and structural delicacy.To generate complete and detailed models of this architecture,it is better to acquire,process,and fuse multi-source data instead of single-source data.In this paper,we describe our work on 3D digital preservation of ancient Chinese architecture based on multi source data.We first briefly introduce two surveyed ancient Chinese temples,Foguang Temple and Nanchan Temple.Then,we report the data acquisition equipment we used and the multi-source data we acquired.Finally,we provide an overview of several applications we conducted based on the acquired data,including ground and aerial image fusion,image and LiDAR(light detection and ranging)data fusion,and architectural scene surface reconstruction and semantic modeling.We believe that it is necessary to involve multi-source data for the 3D digital preservation of ancient Chinese architecture,and that the work in this paper will serve as a heuristic guideline for the related research communities.

Digital Simulation Platform for Satellite Launch Mission Verification

To simulate the satellite launch mission under a general platform which could be used in a full-digital mode as well as in a semi-physical way, is an important way to certify the mission design performance as well as technical feasibilities, and it relates to complex system simulation methods such as multi-disciplinary coupling, multi-language modeling as well as interactive simulation and virtual simulation technologies. This paper introduces the design of a digital simulation platform for satellite launch mission verification.The platform has the advantages of high generality and extensibility, being easy to build up. The Functional Mockup Interface(FMI) Standard is adopted to achieve integration of multi-source models. A WebGL based 3D visual simulation tool is also adopted to implement the virtual display system which could display the rocket launch process and rocket-satellite separation with high fidelity 3D virtual scenes. A configuration tool was developed to map the 3D objects in the visual scene with simulation physical variables for complex rocket flight control mechanisms, which greatly improves the platform's generality and extensibility. Finally the real-time performance had been tested and the YL-1 launch mission was adopted to demonstrate the functions of the platform.The platform will be used to construct a digital twin system for satellite launch missions in the future.

基于DirectX构建虚拟战场环境研究

虚拟战场的构建是当前军事仿真领域中的一个非常前沿性的课题。随着计算机硬件性能的大幅度提高,使得在PC机上利用底层的图形函数接口构建虚拟战场环境也成为可能,从而可以大大降低成本。探讨了D irectX在三维地形模拟、海洋环境仿真、战场特殊效果、自然现象模拟、武器装备动画、人员动作模拟和战场三维真实感声音生成中的应用。比较全面地介绍了利用D irectX构建虚拟战场环境所涉及到的各种技术。

Recent advances in 3D Gaussian splatting

The emergence of 3D Gaussian splatting(3DGS)has greatly accelerated rendering in novel view synthesis.Unlike neural implicit representations like neural radiance fields(NeRFs)that represent a 3D scene with position and viewpoint-conditioned neural networks,3D Gaussian splatting utilizes a set of Gaussian ellipsoids to model the scene so that efficient rendering can be accomplished by rasterizing Gaussian ellipsoids into images.Apart from fast rendering,the explicit representation of 3D Gaussian splatting also facilitates downstream tasks like dynamic reconstruction,geometry editing,and physical simulation.Considering the rapid changes and growing number of works in this field,we present a literature review of recent 3D Gaussian splatting methods,which can be roughly classified by functionality into 3D reconstruction,3D editing,and other downstream applications.Traditional point-based rendering methods and the rendering formulation of 3D Gaussian splatting are also covered to aid understanding of this technique.This survey aims to help beginners to quickly get started in this field and to provide experienced researchers with a comprehensive overview,aiming to stimulate future development of the 3D Gaussian splatting representation.

Deep panoramic depth prediction and completion for indoor scenes

We introduce a novel end-to-end deeplearning solution for rapidly estimating a dense spherical depth map of an indoor environment.Our input is a single equirectangular image registered with a sparse depth map,as provided by a variety of common capture setups.Depth is inferred by an efficient and lightweight single-branch network,which employs a dynamic gating system to process together dense visual data and sparse geometric data.We exploit the characteristics of typical man-made environments to efficiently compress multiresolution features and find short-and long-range relations among scene parts.Furthermore,we introduce a new augmentation strategy to make the model robust to different types of sparsity,including those generated by various structured light sensors and LiDAR setups.The experimental results demonstrate that our method provides interactive performance and outperforms stateof-the-art solutions in computational efficiency,adaptivity to variable depth sparsity patterns,and prediction accuracy for challenging indoor data,even when trained solely on synthetic data without any fine tuning.

SinGRAV: Learning a Generative Radiance Volume from a Single Natural Scene

We present SinGRAV, an attempt to learn a generative radiance volume from multi-view observations of a single natural scene, in stark contrast to existing category-level 3D generative models that learn from images of many object-centric scenes. Inspired by SinGAN, we also learn the internal distribution of the input scene, which necessitates our key designs w.r.t. the scene representation and network architecture. Unlike popular multi-layer perceptrons (MLP)-based architectures, we particularly employ convolutional generators and discriminators, which inherently possess spatial locality bias, to operate over voxelized volumes for learning the internal distribution over a plethora of overlapping regions. On the other hand, localizing the adversarial generators and discriminators over confined areas with limited receptive fields easily leads to highly implausible geometric structures in the spatial. Our remedy is to use spatial inductive bias and joint discrimination on geometric clues in the form of 2D depth maps. This strategy is effective in improving spatial arrangement while incurring negligible additional computational cost. Experimental results demonstrate the ability of SinGRAV in generating plausible and diverse variations from a single scene, the merits of SinGRAV over state-of-the-art generative neural scene models, and the versatility of SinGRAV by its use in a variety of applications. Code and data will be released to facilitate further research.

Perspectives on point cloud-based 3D scene modeling and XR presentation within the cloud-edge-client architecture

With the support of edge computing,the synergy and collaboration among central cloud,edge cloud,and terminal devices form an integrated computing ecosystem known as the cloud-edge-client architecture.This integration unlocks the value of data and computational power,presenting significant opportunities for large-scale 3D scene modeling and XR presentation.In this paper,we explore the perspectives and highlight new challenges in 3D scene modeling and XR presentation based on point cloud within the cloud-edge-client integrated architecture.We also propose a novel cloud-edge-client integrated technology framework and a demonstration of municipal governance application to address these challenges.

When a tree model meets texture baking:an approach for quality-preserving lightweight visualization in virtual 3D scene construction

Three-dimensional(3D)high-fidelity surface models play an important role in urban scene construction.However,the data quantity of such models is large and places a tremendous burden on rendering.Many applications must balance the visual quality of the models with the rendering efficiency.The study provides a practical texture baking processing pipeline for generating 3D models to reduce the model complexity and preserve the visually pleasing details.Concretely,we apply a mesh simplification to the original model and use texture baking to create three types of baked textures,namely,a diffuse map,normal map and displacement map.The simplified model with the baked textures has a pleasing visualization effect in a rendering engine.Furthermore,we discuss the influence of various factors in the process on the results,as well as the functional principles and characteristics of the baking textures.The proposed approach is very useful for real-time rendering with limited rendering hardware as no additional memory or computing capacity is required for properly preserving the relief details of the model.Each step in the pipeline is described in detail to facilitate the realization.

用Director MX实现虚拟场景漫游

实现虚拟场景漫游的主要技术包括场景建模和程序设计两个方面,利用贴图和建模相结合建立模型可以大大简化模型,利用Director MX导入Shockwave 3D演员,并应用Director的3D行为能够很方便的控制三维模型以实现场景漫游,文章以简单游戏场景漫游为例介绍了这种方法的具体实现。

Generation and Control of Game Virtual Environment

In this paper, we present a framework for the generation and control of an Internet-based 3-dimensional game virtual environment that allows a character to navigate through the environment. Our framework includes 3-dimensional terrain mesh data processing, a map editor, scene processing, collision processing, and walkthrough control. We also define an environment-specific semantic information editor, which can be applied using specific location obtained from the real world. Users can insert text information related to the characters real position in the real world during navigation in the game virtual environment.