Terrain Simplification Research in Augmented Scene Modeling

Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the 'short-sight' problem associated with the traditional methods.

Structured scene modeling using micro stereo vision system with large field of view

This paper presents a method for structured scene modeling using micro stereo vision system with large field of view. The proposed algorithm includes edge detection with Canny detector, line fitting with principle axis based approach, finding corresponding lines using feature based matching method, and 3D line depth computation.

Fuzzy-based indoor scene modeling with differentiated examples

Well-designed indoor scenes incorporate interior design knowledge,which has been an essential prior for most indoor scene modeling methods.However,the layout qualities of indoor scene datasets are often uneven,and most existing data-driven methods do not differentiate indoor scene examples in terms of quality.In this work,we aim to explore an approach that leverages datasets with differentiated indoor scene examples for indoor scene modeling.Our solution conducts subjective evaluations on lightweight datasets having various room configurations and furniture layouts,via pairwise comparisons based on fuzzy set theory.We also develop a system to use such examples to guide indoor scene modeling using user-specified objects.Specifically,we focus on object groups associated with certain human activities,and define room features to encode the relations between the position and direction of an object group and the room configuration.To perform indoor scene modeling,given an empty room,our system first assesses it in terms of the user-specified object groups,and then places associated objects in the room guided by the assessment results.A series of experimental results and comparisons to state-of-the-art indoor scene synthesis methods are presented to validate the usefulness and effectiveness of our approach.

3D indoor scene modeling from RGB-D data:a survey

3D scene modeling has long been a fundamental problem in computer graphics and computer vision. With the popularity of consumer-level RGB-D cameras,there is a growing interest in digitizing real-world indoor 3D scenes. However,modeling indoor3 D scenes remains a challenging problem because of the complex structure of interior objects and poor quality of RGB-D data acquired by consumer-level sensors.Various methods have been proposed to tackle these challenges. In this survey,we provide an overview of recent advances in indoor scene modeling techniques,as well as public datasets and code libraries which can facilitate experiments and evaluation.

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.

Modeling of Irregular Structures in Scene Simulation Based on Creator and 3dsmax

Creating proper 3D models plays an important pole in the development of scene simulation system based on multigen creator and Vega software. However, it is very difficult to construct complex structures by multigen creator. In this paper, an approach is proposed which is utilizing 3dsmax as assistant modeling software. 3D models developed in 3dsmax could be saved in 3ds format and then imported into multigen creator software. The models are revised and then saved in fit format by creator. For reducing model＇s data, simplification strategy is proposed. The problem of constructing complex models in creator is solved smoothly. In the development of digital rocket simulation project, the models constructed by this method have good visual effect, small size, and could be driven by Vega correctly.

Research on Motion Attention Fusion Model-Based Video Target Detection and Extraction of Global Motion Scene

For target detection algorithm under global motion scene, this paper suggests a target detection algorithm based on motion attention fusion model. Firstly, the motion vector field is pre-processed by accumulation and median filter;Then, according to the temporal and spatial character of motion vector, the attention fusion model is defined, which is used to detect moving target;Lastly, the edge of video moving target is made exactly by morphologic operation and edge tracking algorithm. The experimental results of different global motion video sequences show the proposed algorithm has a better veracity and speedup than other algorithm.

Semantic Driven Design Reuse for 3D Scene Modeling

The increasing scale and complexity of 3D scene design work urge an efficient way to understand the design in multi-disciplinary team and exploit the experiences and underlying knowledge in previous works for reuse.However the previous researches lack of concerning on relationship maintaining and design reuse in knowledge level.We propose a novel semantic driven design reuse system,including a property computation algorithm that enables our system to compute the properties while modeling process to maintain the semantic consistency,and a vertex statics based algorithm that enables the system to recognize scene design pattern as universal semantic model for the same type of scenes.With the universal semantic model,the system conducts the modeling process of future design works by suggestions and constraints on operation.The proposed framework empowers the reuse of 3D scene design on both model level and knowledge level.

基于ArcScene三维数字流域建模研究

三维数字流域是对流域周边地理环境、自然环境和生态环境等各种信息的直观显示,对流域内经济建设与资源利用有重要的辅助作用。该研究提出了一种基于Arc Scene的三维数字流域建模方法。利用航空摄影测量获得的高分辨率的DOM影像与DEM数据进行叠加分析,实现了数字流域的建模与多视图的三维飞行动画预览。利用该方法可以对流域内地形地貌与人文特征进行快速直观的预览与分析,为流域内水利设施、交通设施、社会公共设施的设计施工与改建的顺利进行提供重要的技术支持。

基于ArcScene与SketchUp交互建模技术的生态景观开发——以当阳市庙前镇关雎河畔为例

以当阳市庙前镇关雎河畔为例,重点介绍了基于ArcScene与SketchUp交互建模技术:基于SketchUp Esri插件和基于ArcScene中3D编辑器的交互建模技术,并比较两种不同建模技术之间的优缺点和适用范围,同时应用带有高程值的航拍地形数据点要素模拟关雎河畔地形,对场景精细化以完成生态景观场景开发。

基于Dp-Modeler平台的空地一体化三维实景建模

倾斜摄影技术近地面的三维实景模型常出现变形、缺失等问题,而地面影像辅助倾斜摄影影像能够获得更加精细、完整的三维模型。基于Dp-Modeler平台,利用GPS辅助空三算法,解决了空地影像联合对地面影像定姿的问题,实现了倾斜影像与地面影像数据的耦合。

基于OpenSceneGraph的大场景三维浏览系统设计与实现

文中主要研究了基于OpenSceneGraph的大场景三维模型的建立、三维浏览系统设计与实现。首先在3DMax中建立场景中的独立模型,利用VirtualPlanetBuilder建立场景DEM模型,最后利用Visual Stidio和OpenSceneGraph设计并开发了大场景三维浏览系统,实现了三维场景模型的加载、浏览和漫游功能。

基于DP-Modeler的建筑物三维建模

针对建筑物三维模型构建过程中细节缺失、成本较高、效率低下的问题,本文采用倾斜辅助人工建模技术,利用倾斜影像,基于DP-Modeler软件实现建筑物的建模,且与其他建模方法进行比较,采用倾斜辅助人工所建模型保持了建筑物的细节信息,适用于大范围精细模型场景,且提高了建筑物的建模效率,降低了设备成本。

A Solely Radiance-based Spectral Angular Distribution Model and Its Application in Deriving Clear-Sky Spectral Fluxes over Tropical Oceans

The radiation budget at the top of the atmosphere plays a critical role in climate research. Compared to the broadband flux, the spectrally resolved outgoing longwave radiation or flux （OLR）, with rich atmospheric information in different bands, has obvious advantages in the evaluation of GCMs. Unlike methods that need auxiliary measurements and information, here we take atmospheric infrared sounder （AIRS） observations as an example to build a self-consistent algorithm by an angular distribution model （ADM）, based solely on radiance observations, to estimate clear-sky spectrally resolved fluxes over tropical oceans. As the key step for such an ADM, scene type estimations are obtained from radiance and brightness temperature in selected AIRS channels. Then, broadband OLR as well as synthetic spectral fluxes are derived by the spectral ADM and validated using both synthetic spectra and CERES （Clouds and the Earth＇s Radiant Energy System） observations. In most situations, the mean OLR differences between the spectral ADM products and the CERES observations are within -4-2 W m-2, which is less than 1% of the typical mean clear-sky OLR over tropical oceans. The whole algorithm described in this study can be easily extended to other similar hyperspectral radiance measurements.

面向水库型小流域的多源水利三维建模方法研究

针对大型河道三维可视化建模中采用激光雷达、声呐等传感器获取水下地形建模方式操作复杂且成本较高的缺陷,在利用基础测绘成果构建实景地形模型的基础上,采用多源三维模型融合方法对月塘水库小流域进行实景建模。首先采用倾斜摄影三维建模技术对重点水利工程进行实景建模,并利用专业建模软件对重要控制单元进行构件级建模;然后利用已有河道断面数据结合河流面状矢量数据,实现流域内胥浦河河道实景三维建模;最后通过人机交互方式对多源实景模型进行微调与相互印证,实现月塘水库小流域多源三维模型精准融合构建。研究成果可为河道型水库的预报调度与洪水风险分析提供可视化模型基础与决策支撑。

Natural Scene Classification Inspired by Visual Perception and Cognition Mechanisms

The process of human natural scene categorization consists of two correlated stages: visual perception and visual cognition of natural scenes.Inspired by this fact,we propose a biologically plausible approach for natural scene image classification.This approach consists of one visual perception model and two visual cognition models.The visual perception model,composed of two steps,is used to extract discriminative features from natural scene images.In the first step,we mimic the oriented and bandpass properties of human primary visual cortex by a special complex wavelets transform,which can decompose a natural scene image into a series of 2D spatial structure signals.In the second step,a hybrid statistical feature extraction method is used to generate gist features from those 2D spatial structure signals.Then we design a cognitive feedback model to realize adaptive optimization for the visual perception model.At last,we build a multiple semantics based cognition model to imitate human cognitive mode in rapid natural scene categorization.Experiments on natural scene datasets show that the proposed method achieves high efficiency and accuracy for natural scene classification.

基于双尺度海谱的动态海面场景仿真建模分析

针对典型复杂环境下动态海面目标场景,采用双尺度海谱用于风驱海面的建模构建公里级别复杂场景电磁仿真模型,研究面向体-面复合结构的自适应弹跳射线法,结合区域分解和并行加速技术实现典型目标及地物环境的耦合电磁散射特性分析,形成公里级别复杂场景多维复合散射特性仿真能力,实现大场景复杂环境与目标一体化模型的高效电磁散射计算与分析。通过测量海面邮轮在实际海面背景下的电磁散射特性,进行验证,为复杂海面背景下大尺度目标的动态场景生成和目标特性研究提供重要支撑作用。

场景理论视域下地铁列车旅客界面需求研究

目的 为了提高乘客在地铁车厢内的乘车体验,优化地铁列车旅客界面的合理性与便捷性。方法 以场景理论为基础,采用问卷调查和用户访谈等方法,收集现有地铁乘客的用户需求,提炼客观场景。运用Kano模型明确地铁旅客界面设计的用户需求权重,基于对用户需求权重的考量及QFD质量屋展开,功能需求被转化为产品特征,用以分析用户需求与产品特征之间的关系。结果 归纳了典型地铁乘车场景,构建地铁列车乘客界面的用户需求与产品特征之间的关联矩阵,并以此为基础分别从车厢布局、信号灯提示、扶握系统和导视系统四个方面,提出了地铁列车旅客界面的配置策略。结论 从场景分析的角度结合多重定量、定性分析方法,验证场景理论对挖掘地铁乘车需求具有一定指导作用,并提出地铁列车旅客界面在提升旅客乘车体验方面的初步建议。

基于边塌陷减面的实景三维模型轻量化技术

实景三维模型由于其丰富的场景展现能力,广泛应用在数字孪生和地理测绘等领域。然而,丰富的三维场景和细节所包含的数据量十分庞大,给实景三维模型的存储、传输、渲染与展示带来了极大的挑战。针对上述问题,本文提出了一种面向实景三维模型的轻量化处理方法,首先引入模型预处理技术,去除模型噪音和非流行边;然后通过边塌陷减面的轻量化算法,精简模型拓扑结构;最后加入反转检测算法,防止边塌陷过程中出现面反转的情况。对张家界景区4个真实场景的测试结果表明,该技术可以在保留模型整体外观和场景细节的基础上,压缩至原始模型大小的3.7%~10.9%,使得复杂场景的实景三维模型能够在计算机中更加快速真实地反映或显示世界的地理地貌或城市建筑。

基于可调场景语义标注范围的家庭室内语义地图构建

针对家庭室内环境语义地图建图速度较慢和在门口场景语义标注易出现错误等问题,提出一种基于可调场景语义标注范围的家庭室内语义地图构建方法。首先根据YOLOv5s识别的物体大小赋予相应的场景置信度,基于该场景置信度设置阈值使得语义标注范围限制在机器人当前所在区域,确保场景切换时语义标注范围不会立即改变。然后基于人工势场虚拟力“引力斥力”原理,实现语义标注范围的扩大或缩小。最后结合阈值和动态语义标注范围,避免在门口场景中出现语义标注错误。实验结果表明:与Places205-VGG16神经网络建立家庭室内语义地图相比,所提方法平均效率和平均精准率分别提升了11.0%和7.8%,在家庭室内环境中具有一定的优越性。