Rapid and Automatic Reconstruction of Large-scale Areas

近年来，对表示包括地形、建筑物、树木、汽车等的大规模真实世界区域的真实虚拟世界的需求不断增加。已经报道了许多采用这种真实虚拟表示的成功应用，包括用于培训应急响应人员的高级灾害管理模拟、在用于城市规划和开发的建设之前就地可视化新结构、以及其中故事情节发生在实际位置而不是虚构位置的计算机游戏。例如，育碧的“刺客信条”包含许多文化遗产遗址[尽管其中一些不是完好无损的]，如索菲亚圣殿、加拉塔、基里尼亚和利马索尔的城堡等。 然而，尽管该领域的工作量很大，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，模型的制作仍然被广泛视为一门专门的艺术，需要有广泛培训和经验的人员来制作有用的模型。基础研究对于弥合当前最先进的技术和快速自动创建大规模区域的最终目标之间的差距是必不可少的。 这项建议解决了目前大规模区域快速和自动重建的技术困难，并寻求解决方案，以开发准确、健壮和可扩展的方法和系统来处理由主动和被动传感器捕获的大数据，以产生逼真的虚拟表示。更具体地说，研究计划建议进一步研究和开发新的和健壮的算法，以准确地检测和提取： (A)从被动和主动遥感传感器(即航空/卫星图像和激光雷达)捕获的数据中获取的结构信息，并重建代表所获区域的地形、建筑物、汽车和树木模型的几何形状， (B)从地面、倾斜航空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三维模型的真实合成纹理地图集中。 这一研究计划有望为解决现实虚拟世界创造领域中具有高度现实意义的复杂问题做出实质性贡献。它还将有助于开发计算机视觉、计算机图形学和计算机游戏等一般领域的创新方法。

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.