3D Augmented Urban Space Modeling for Smart City
智慧城市 3D 增强城市空间建模
基本信息
- 批准号:RGPIN-2014-04173
- 负责人:
- 金额:$ 1.6万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2017
- 资助国家:加拿大
- 起止时间:2017-01-01 至 2018-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
3D reconstruction of indoor and outdoor buildings is an increasingly important research problem, with large scale efforts underway to recover outdoor models of cities at a global scale (e.g. Google Earth). Unfortunately these models are limited in applications and their true potential not realized. There is also a severe lack of knowledge and understanding in indoor and utility (i.e. power line network) modeling which significantly hinder movements for pushing forward with these semantically rich 3D spatial models for engineering and commercial purposes. One such applications involve the augmentation of the 3D models to urban Information and Communication Technologies (ICT) for providing real time decision support and spatial awareness. These augmented 3D models serve as important model-centric interfaces that could result in unprecedented opportunities for efficiently monitoring and managing infrastructures for supporting urban sustainability and elevating the competitiveness of cities which account for nearly 90% of global population growth, 80% of wealth creation, and 60% of total energy consumption [1].In this current Discovery proposal we propose a comprehensive approach to developing a novel 3D framework with potential applications toward urban sustainability and smart city. By extending and advancing our on-going research for modeling of 3D urban spaces, including building and infrastructure modeling, we will develop innovative techniques for integrating the 3D urban space models and delivering real-time information through augmentation. The objective include 1) creating an innovative crowd-sourced modeling approach that is suitable for large scale generation of indoor models. 2) Enhancing the existing suspension type power line network mapping system to model a wide range of line types through expanding our inventory database. 3) we will develop 3D model-based mobile augmented reality (MAR) applications for indoor and outdoor building environments by introducing an original 3D building model-to-image alignment technique and a new hierarchical Geometric Hash table based on quadtree structure for performing accurate localization. Our grand goal for this research program is to develop and implement a framework for large scale augmented urban space model that includes above and underground facilities, natural objects, and man-made indoor/outdoor structures. The integration of high quality 3D indoor and outdoor urban space models augmented with data from systems such as Building Information Model (BIM) will be significant for moving towards a spatial and context-aware society. Ultimately we aim to remove the gap between virtual and physical spaces where they can be considered as part of a continuum in the same dimension for supporting urban sustainability and smart city.Spatial and context-awareness is the trend for future 3D modeling and augmentation researches as advancements in mobile computing technologies continue to blur the line between virtual and physical spaces. Applications such as MAR recognize and react to the real world content and combine users’ view of reality with location specific information. Such information could be in the form of simple text, image, multi-media, or 3D graphics. Whether it is for facility management, urban planning, navigation, tourism and exploration, such augmented information will provide users with information (in real time) for better decision making on-the-go.
室内和室外建筑物的3D重建是一个越来越重要的研究问题,正在进行大规模的努力,以恢复全球范围内的城市室外模型(例如Google Earth)。不幸的是,这些模型在应用中受到限制,其真正的潜力没有实现。在室内和公用事业(即电力线网络)建模方面也严重缺乏知识和理解,这严重阻碍了推进这些语义丰富的3D空间模型用于工程和商业目的的运动。一个这样的应用涉及到城市信息和通信技术(ICT)的三维模型的增强,以提供真实的时间决策支持和空间意识。这些增强的3D模型作为重要的以模型为中心的界面,可以带来前所未有的机会,有效地监测和管理基础设施,以支持城市可持续发展,提高城市的竞争力,这些城市占全球人口增长的近90%,财富创造的80%,和60%的总能耗[1]。在当前的Discovery提案中,我们提出了一种全面的方法来开发一种新型的3D框架,该框架具有城市可持续性和智慧城市的潜在应用。通过扩展和推进我们正在进行的3D城市空间建模研究,包括建筑和基础设施建模,我们将开发创新技术,用于集成3D城市空间模型并通过增强提供实时信息。目标包括:1)创建一种创新的众包建模方法,适用于大规模生成室内模型。2)透过扩充我们的库存数据库,加强现有的悬挂式电力线网络映射系统,以模拟广泛的线路类型。3)我们将通过引入原始的3D建筑物模型到图像对准技术和基于四叉树结构的新的分层几何哈希表来执行精确定位,从而开发用于室内和室外建筑物环境的基于3D模型的移动的增强现实(MAR)应用。本研究计划的宏伟目标是开发和实施一个大规模增强城市空间模型的框架,包括地上和地下设施,自然物体和人造室内/室外结构。将高质量的室内和室外城市空间模型与建筑信息模型(BIM)等系统的数据相结合,对于迈向空间和环境感知社会具有重要意义。最终我们的目标是消除虚拟空间和物理空间之间的差距,使它们可以被视为同一维度上的连续体的一部分,以支持城市的可持续性和智慧城市。随着移动的计算技术的进步不断模糊虚拟空间和物理空间之间的界限,空间和上下文感知是未来3D建模和增强研究的趋势。诸如MAR的应用识别真实的世界内容并对其作出反应,并且将联合收割机用户的现实视图与位置特定信息相结合。这些信息可以是简单的文本、图像、多媒体或3D图形的形式。无论是用于设施管理、城市规划、导航、旅游和探索,这种增强的信息都将为用户提供(真实的时间)信息,以便在行进中做出更好的决策。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Sohn, Gunho其他文献
High-density stereo image matching using intrinsic curves
- DOI:
10.1016/j.isprsjprs.2018.10.005 - 发表时间:
2018-12-01 - 期刊:
- 影响因子:12.7
- 作者:
Shahbazi, Mozhdeh;Sohn, Gunho;Theau, Jerome - 通讯作者:
Theau, Jerome
A Piecewise Catenary Curve Model Growing for 3D Power Line Reconstruction
- DOI:
10.14358/pers.78.11.1227 - 发表时间:
2012-12-01 - 期刊:
- 影响因子:1.3
- 作者:
Jwa, Yoonseok;Sohn, Gunho - 通讯作者:
Sohn, Gunho
Point-based Classification of Power Line Corridor Scene Using Random Forests
- DOI:
10.14358/pers.79.9.821 - 发表时间:
2013-09-01 - 期刊:
- 影响因子:1.3
- 作者:
Kim, Heungsik B.;Sohn, Gunho - 通讯作者:
Sohn, Gunho
Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction
- DOI:
10.1016/j.isprsjprs.2007.01.001 - 发表时间:
2007-05-01 - 期刊:
- 影响因子:12.7
- 作者:
Sohn, Gunho;Dowman, Ian - 通讯作者:
Dowman, Ian
Tree genera classification with geometric features from high-density airborne LiDAR
- DOI:
10.5589/m13-024 - 发表时间:
2013-12-01 - 期刊:
- 影响因子:2.6
- 作者:
Ko, Connie;Sohn, Gunho;Remmel, Tarmo K. - 通讯作者:
Remmel, Tarmo K.
Sohn, Gunho的其他文献
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{{ truncateString('Sohn, Gunho', 18)}}的其他基金
3D Intelligent Spatial Modeling for Infrastructure Digital Twins
基础设施数字孪生的 3D 智能空间建模
- 批准号:
RGPIN-2020-07144 - 财政年份:2022
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
3D Mobile Mapping Using Artificial Intelligence
使用人工智能的 3D 移动测绘
- 批准号:
537080-2018 - 财政年份:2021
- 资助金额:
$ 1.6万 - 项目类别:
Collaborative Research and Development Grants
3D Intelligent Spatial Modeling for Infrastructure Digital Twins
基础设施数字孪生的 3D 智能空间建模
- 批准号:
RGPIN-2020-07144 - 财政年份:2021
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
3D Intelligent Spatial Modeling for Infrastructure Digital Twins
基础设施数字孪生的 3D 智能空间建模
- 批准号:
RGPIN-2020-07144 - 财政年份:2020
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
3D Mobile Mapping Using Artificial Intelligence
使用人工智能的 3D 移动测绘
- 批准号:
537080-2018 - 财政年份:2020
- 资助金额:
$ 1.6万 - 项目类别:
Collaborative Research and Development Grants
3D Mobile Mapping Using Artificial Intelligence
使用人工智能的 3D 移动测绘
- 批准号:
537080-2018 - 财政年份:2019
- 资助金额:
$ 1.6万 - 项目类别:
Collaborative Research and Development Grants
3D Augmented Urban Space Modeling for Smart City
智慧城市 3D 增强城市空间建模
- 批准号:
RGPIN-2014-04173 - 财政年份:2018
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
Automatic railway inspection and inventory updating using a compact mobile laser scanner
使用紧凑型移动激光扫描仪进行自动铁路检查和库存更新
- 批准号:
492660-2015 - 财政年份:2017
- 资助金额:
$ 1.6万 - 项目类别:
Collaborative Research and Development Grants
3D Augmented Urban Space Modeling for Smart City
智慧城市 3D 增强城市空间建模
- 批准号:
RGPIN-2014-04173 - 财政年份:2016
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
Evaluation of traffic sign retroreflectivity measurement using mobile LiDAR
使用移动激光雷达评估交通标志逆反射率测量
- 批准号:
484404-2015 - 财政年份:2015
- 资助金额:
$ 1.6万 - 项目类别:
Engage Grants Program
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