多層次精緻度三維房屋模型之建置; Level of detail generation of 3D building models

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題名:	多層次精緻度三維房屋模型之建置;Level of detail generation of 3D building models
作者:	林宛蓉;Wan-jung Lin
貢獻者:	土木工程研究所
關鍵詞:	三維房屋模型簡化;視覺模擬;數碼城市;精緻度層級;cyber city;visualization;3D building generalization;Level of Detail
日期:	2009-06-22
上傳時間:	2009-09-18 17:27:57 (UTC+8)
出版者:	國立中央大學圖書館
摘要:	三維房屋模型是重建都市景觀最重要的元件之一。但龐大的房屋模型資料會降低應用系統的整體效能。為了在數碼城市中達成互動式的視覺模擬效果與即時顯像的功能，建置多層次精緻度模型(Level of Detail, LOD)為常用來減少非必要顯像的處理方法。經由建置不同精緻度的模型，視覺模擬系統可依據使用者不同的視覺條件挑選最適合精緻度層級之模型顯像，加速整體系統處理效能。本研究即針對三維多面體房屋模型，提出一半自動簡化方法，建置三維房屋之多層次精緻度模型，以增進數碼城市即時視覺模擬及應用之效率。本研究之主要構想為利用房屋建築三視圖概念，經由簡化三維房屋模型之多方向二維投影，改變房屋模型之幾何型態，再重組以建置多層次精緻度三維房屋模型。首先，透過房屋模型之幾何結構分析決定房屋模型需進行之簡化層數，以及是否包含非平頂之屋頂結構。對於欲簡化之房屋模型以正射投影產生不同方向之二維投影面。為建立投影面外圍輪廓之位相關係，本研究引用並改良網格化及TDGO運算子，開發投影面前處理演算法進行處理。二維投影面簡化流程即利用前處理所得二維投影面之位相關係計算各投影面上各線段之長度及相對角度，針對投影面上各線段進行正規化流程及移除符合簡化門檻值之U型、Z型、L型結構。再透過本研究開發以布林運算子為基礎之組合演算法，將簡化投影面重組為低精緻度三維房屋模型。對於房屋中之特殊結構，如非平頂屋頂結構、中庭構造及非平面牆面結構，本研究以半自動之額外處理方式對特殊結構進行簡化並維持其特徵。最後，將處理後之特殊結構與已簡化之平頂(牆面)主體模型組合後即完成三維房屋模型簡化程序。本研究測試兩組不同類型之大範圍房屋群，測區位於中央大學及台北市信義區。檢視個別房屋模型之實驗成果驗證顯示，本研究所提出以二維投影面簡化三維房屋模型之方式，可有效簡化三維房屋之幾何結構。而將本研究方法應用於大範圍之房屋群，實驗成果則證明本研究方法在不同精緻度層級皆可有效降低整體房屋模型之總點數及總面數。此外，本研究所提出處理三維房屋模型中特殊結構之方法的確可在簡化房屋模型後仍維持房屋模型之重要可視特徵。 Three dimensional (3D) building model is one of the most important components in the construction and representation of urban scenes. In application systems, the vast amount of building data may lead to lower efficiency. For interactive visualization and real-time rendering in cyber city applications, Level of Detail (LOD) technique is a common approach to reduce unnecessary computations. LOD technique can generate different details of data and set appropriate levels according to viewing parameters to enhance visualization system performance. This research proposes a semi-automatic approach for the generalization of 3D polyhedral building models to formulate LOD representations of complicated buildings for high performance visualization of cyber city. The idea is to apply generalization in 2D orthographic views of 3D building models. First, (geometric) structure analysis is conducted to compute shape complexity for determining the number of levels to generalize and to detect non-planar roof structures. For building models to generalize, orthographic views along different directions of the 3D building geometries are generated. To construct the topology of orthographic views, rasterization techniques and modified quasi-Target Defined Ground Operator (quasi-TDGO) are used in pre-processing of orthographic views. By calculating the lengths and angles with the topology, the edge regularization and U-, Z-, L-structures elimination are employed to generalize 2D orthographic views. Simplified 3D models are reconstructed from generalized 2D orthographic views with Boolean-based algorithms. For special structures of building models, such as buildings with non-planar roof structures, courtyards, and curved elements, additional processes are developed to simplify them but maintain their characteristics. Finally, these special structures are combined with reconstructed façades to complete the generalization of 3D building models. Two groups of complex building models in National Central University (NCU) campus and the Xinyi District of Taipei city are used to test the developed building generalization algorithms. Experimental results of single building models demonstrate that the proposed method can effectively simplify 3D building geometries with generalized 2D orthographic views of building models. For building groups in large areas, the proposed method is effective in decreasing the number of points and polygons of building groups in different levels. In addition, the experimental results of building models with special structures are also validated, proving that the proposed approach can preserve important visual characteristics of complicated building models.
顯示於類別:	[土木工程研究所] 博碩士論文

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