A Geometry-and Image-based Hybrid Modeling And Visually Lossless Rendering Approach For Large-scale Urban Simulation

Urban simulation and visualization are the bases of digital city and intelligentcity systems, and also important to a variety of stakeholders such as virtualgeographics information system, urban planning, and intelligent transportation, etc.Rendering large-scale urban scenes requires an integration of3D city modeling, hugedata processing, and complex scenes rendering theories. The graphics processing unitneeds to work synchronously with the rest of the computer, and it requireshigh-performance access to a huge mount of spatial data thus provides high realisticrendering results through real-time computation and visualization.The key observation of our research is large-scale urban scenes simulationusually prone to huge data modeling and rendering issues. Firstly, rendering urbandataset requires a processing of large-scale geometric primitives and textures. How toreduce the amounts of data thus achieve the balance on visual quality and datacomplexity, and the implemention of efficient data storage, dispatching andtransmission on CPU-GPU heterogeneous system architecture are major bottlenecksin this field. Secondly, how to implement high performance urban visualization whichmaintains plausible visual quality and provides high realistic results is also an openproblem.The objective of this study is archieving visually lossless rendering of large-scaleurban scenes and resovling the critical issues in the field of urban visualization asmentioned above. Firstly, an inverse procedual modeling approach is introduced forurban textures modeling, and then seamlessly integrated with geometic models andprovides hybrid geometry-and image-based representation for3D urban modeling;secondly, a progressive hybrid level-of-detail representation which combines points-,lines-and splats-based models and created through multi-jittered sampling andrecursive Wang-Tiles is proposed; thirdly, an urban scenes oriented3D spatial dataengine is introduced for resolving the performance and throughout bottlenecksbetween hard drive, main memory and video memory; furthermore, a comprehensive visual quality accessment which combines cognitive psychology, statistics models,pattern recognition and computer graphics theories is established for evaluatingperceptual changes in the outputs of computer graphics applications. Theexperimental results confirmed that the visual quality of our urban visualizationsystem is indistinguishable from the original models.The main contributions of this study are as follow:1) A novel procedural representation for facade textures. It can be seemlesslyinteraged with geometries to create hybrid3D urban models. The user-assisted inverseprocedural modeling approach allows user to exploit repetations and symmetries offacades to create a splite grammar of the input and remove the occlusions in anefficient way. The procedural textures can be direcly reconstructed in GPU, so noextra rendering passes and geometries are introduced. Comparing with the geometiclevel-of-details, the hybrid of geometry and procedural facade modeling achieved acompression factor that averaged70%and improved the rendering performance by20%.2) A novel hybrid level-of-detail approach for large-scale urban scenesrendering. We combine point-, lines-and splat-based rendering to synthesizelarge-scale urban city images with high visual quality. The algorithm usesscreen-space projected area as a progressive LOD selector and saves large amounts ofmemory spaces by avoiding textures. Our implementation shows a10times speed-upas compared to the ground truth models rendered as full geometry, and is about4times faster compared to geometic LOD. The quality of the results is alsoindistinguishable from the originals as confirmed by a comprehensive visual qualityassessment metric for computer graphics applications. The assessment modelintegrates subjective perceptual user study and two objective algorithm-based metrics,thus implements evaluation and numeralization on human visual responses.3) Design and implementation of an urban oriented3D spatial data enginewhich is capable for working under CPU-GPU heterogeneous system architecture.High performance spatial querying is archived by the use of Cell-Rtree spatialindexing and Hilbert storage indexing algorithms.3D spatial data exchanging,dispatching and caching strategies, as well as threads pools and memory management models are also proposed for improving I/O performance in large-scale visualizationsystems. The spatial data engine could also be an important component for visuallylossless urban scenes rendering.