Rapid and Automatic Reconstruction of Large-scale Areas
大范围区域快速自动重建
基本信息
- 批准号:RGPIN-2016-06689
- 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:2016
- 资助国家:加拿大
- 起止时间:2016-01-01 至 2017-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
In recent years there has been an increasing demand for realistic virtual worlds representing large-scale, real-world areas comprising of terrain, buildings, trees, cars, etc. Many successful applications employing such realistic virtual representations have already been reported including advanced disaster management simulations for the training of emergency response personnel, visualizing new structures in-situ prior to construction for urban planning and development, and computer games where the storyline takes place in an actual rather than fictional location. For example Ubisoft’s "Assassin’s Creed" contains numerous cultural heritage sites [albeit some of them not in perfect condition], such as the Hagia Sophia, the Galata tower, the castles in Kyrenia and Limassol, etc.
However, despite the large volume of work in the area many challenges still remain. Currently, the creation of realistic large-scale 3D content remains a complex, time-consuming, expensive and labor-intensive task. In fact, the creation of models is still widely viewed as a specialized art, requiring personnel with extensive training and experience to produce useful models. Fundamental research is essential in order to bridge the gap between the current state-of-the-art and the ultimate goal of rapid and automatic creation of large-scale areas.
This proposal addresses the current technological difficulties of rapid and automatic reconstruction of large scale areas and seeks solutions for the development of accurate, robust and scalable methods and systems for processing the big data captured by active and passive sensors in order to produce a realistic virtual representation. More specifically the research program proposes further study and development of novel and robust algorithms for accurately detecting and extracting:
(a) structural information from data captured from passive and active remote sensors i.e. aerial/satellite images and LiDAR, and reconstructing the geometry of the terrain, buildings, cars and tree models representing the acquired area,
(b) appearance information from imagery captured from ground, oblique-aerial and satellite sensors, and fusing this information into realistic composite texture atlases of the 3D models.
This research program is expected to make substantial contributions to the solution of complex problems of high practical relevance to the field of realistic virtual world creation. It will also contribute to the development of innovative methods in the general fields of computer vision, computer graphics and computer games.
近年来,人们越来越需要逼真的虚拟世界来表示大规模的真实世界区域,包括地形、建筑物、树木、汽车等。已经报道了采用这种逼真的虚拟表示的许多成功应用,包括用于培训应急响应人员的高级灾害管理模拟,在城市规划和发展建设之前在现场可视化新结构,以及故事情节发生在真实而非虚构地点的电脑游戏。例如,育碧的《刺客信条》包含了许多文化遗产[尽管其中一些并不完美],如圣索菲亚大教堂,加拉塔塔,凯里尼亚和利马索尔的城堡等。
然而,尽管这一领域的工作量很大,但仍然存在许多挑战。目前,创建逼真的大规模3D内容仍然是一项复杂、耗时、昂贵和劳动密集型的任务。事实上,模型的创建仍然被广泛认为是一门专业的艺术,需要经过广泛培训和经验的人员来制作有用的模型。基础研究是必不可少的,以弥合当前最先进的水平和快速和自动创建大规模区域的最终目标之间的差距。
该提案解决了当前大规模区域的快速和自动重建的技术难题,并寻求开发用于处理由主动和被动传感器捕获的大数据的准确、鲁棒和可扩展的方法和系统的解决方案,以便产生逼真的虚拟表示。更具体地说,该研究计划提出进一步研究和开发用于准确检测和提取的新颖而强大的算法:
(a)- 从被动和主动遥感器(即航空/卫星图像和激光雷达)捕获的数据中获取结构信息,并重建表示所获取区域的地形、建筑物、汽车和树木模型的几何形状,
(b)从地面、机载和卫星传感器捕获的图像中获取外观信息,并将这些信息融合到3D模型的逼真复合纹理图谱中。
该研究计划预计将为解决现实虚拟世界创建领域具有高度实际相关性的复杂问题做出实质性贡献。它还将有助于在计算机视觉,计算机图形和计算机游戏的一般领域的创新方法的发展。
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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Poullis, Charalambos其他文献
Poullis, Charalambos的其他文献
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{{ truncateString('Poullis, Charalambos', 18)}}的其他基金
Semantic Segmentation in Geospatial Computer Vision
地理空间计算机视觉中的语义分割
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- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
ACESO: Computer Vision Algorithms for Computer-Assisted Surgical Systems
ACESO:计算机辅助手术系统的计算机视觉算法
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567101-2021 - 财政年份:2021
- 资助金额:
$ 1.6万 - 项目类别:
Alliance Grants
Semantic Segmentation in Geospatial Computer Vision
地理空间计算机视觉中的语义分割
- 批准号:
RGPIN-2021-03479 - 财政年份:2021
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
Rapid and Automatic Reconstruction of Large-scale Areas
大范围区域快速自动重建
- 批准号:
RGPIN-2016-06689 - 财政年份:2020
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
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$ 1.6万 - 项目类别:
Department of National Defence / NSERC Research Partnership
Rapid and Automatic Reconstruction of Large-scale Areas
大范围区域快速自动重建
- 批准号:
RGPIN-2016-06689 - 财政年份:2019
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
Rapid and Automatic Reconstruction of Large-scale Areas
大范围区域快速自动重建
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- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
Rapid and Automatic Reconstruction of Large-scale Areas
大范围区域快速自动重建
- 批准号:
RGPIN-2016-06689 - 财政年份:2017
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
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