Context-based automatic reconstruction and texturing of 3D urban terrain for quick-response tasks |
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| Institution: | 1. California National Primate Research Center, University of California, Davis, United States;2. Department of Anatomy, Physiology, and Cell Biology, School of Veterinary Medicine, University of California, Davis, CA, United States;1. Kobe University, 5-1-1, Fukae-minamimachi, Higashinad, a-kuFaculty of Maritime Sciences, 658-0022, Kobe, Japan;2. University of Canterbury, Department of Geological Sciences, Christchurch, New Zealand;1. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, College of Electronic Science, National University of Defense technology, Changsha, Hunan 410003, China;2. University of Oulu, Oulu 90014, Finland;3. Duke University, Durham 27708, USA;4. College of Systems Engineering, National University of Defense technology, Changsha, Hunan 410003, China;1. Chung-Ang University, Seoul, South Korea;2. Hankyong National University, Anseong, South Korea |
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| Abstract: | Highly detailed 3D urban terrain models are the base for quick response tasks with indispensable human participation, e.g., disaster management. Thus, it is important to automate and accelerate the process of urban terrain modeling from sensor data such that the resulting 3D model is semantic, compact, recognizable, and easily usable for training and simulation purposes. To provide essential geometric attributes, buildings and trees must be identified among elevated objects in digital surface models. After building ground-plan estimation and roof details analysis, images from oblique airborne imagery are used to cover building faces with up-to-date texture thus achieving a better recognizability of the model. The three steps of the texturing procedure are sensor pose estimation, assessment of polygons projected into the images, and texture synthesis. Free geographic data, providing additional information about streets, forest areas, and other topographic object types, suppress false alarms and enrich the reconstruction results. |
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| Keywords: | Building detection Building reconstruction Pose estimation Simulation Texturing Urban terrain |
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