博碩士論文 105322075 詳細資訊




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姓名 張凱硯(Kai-Yen Chang)  查詢紙本館藏   畢業系所 土木工程學系
論文名稱 三維房屋模型擬真牆面通用紋理產製及敷貼
(Improving Generic Facade Textures of Building Models for Realistic Visualization)
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摘要(中) 本研究利用街景或測量車等實景影像為參考,改良三維房屋模型的通用紋理貼圖。目的是提高三維數位城市模型視覺化展示時的擬真性,並保有通用紋理貼圖的效能。
研究內容可分成三個部分:(1)影像校正、(2)影像分析與 (3)通用紋理資料庫改良。一開始影像資料需先計算測站、影像與建物三者的共線關係,解算建物在影像之坐標點後視為控制點校正影像幾何。校正完的影像接著可做牆面特徵物分析的演算,解算牆面顏色與窗戶幾何特徵。最後在改良通用紋理資料庫,達到效能友善與部分擬真。
本研究所開發的方法可高度自動化影像前處理、解析牆面窗戶特徵物與牆面顏色,最後再依據這些指標改善原通用紋理資料庫。相較使用隨機挑選的通用紋理,以本研究所開發的方法可達到較擬真的視覺展示,但保有通用紋理對系統的效能友善。
摘要(英) This study tries to improve generic facade textures of building models for realistic look and feel of digital city model visualization. The idea is to use street view or in-situ images as references to produce generic textures that can provide more realistic look and feel of the visualization.
The procedure is separated into (1) image pre-processing, (2) image analysis and (3) improving generic texture database. Collinear relationship of stations, images and buildings could help calculate the coordinates, and these coordinates are viewed as ground control points to rectify image geometry. Also, image analysis parses the facade colors and detects window patterns. Finally, using these features, this study improves the generic texture database to maintain efficiency and provide more realistic scene.
The algorithm developed in this study demonstrates how to process and parse facade images and to improve generic database systematically. The results demonstrate a better performance and realistic look-and-feel comparing to generic textures chosen randomly.
關鍵字(中) ★ 數位城市
★ 通用紋理
★ 牆面紋理分析
關鍵字(英) ★ Cyber City
★ generic textures
★ Facade Parsing
論文目次 摘要 I
Abstract II
致謝 III
目錄 IV
圖目錄 VII
表目錄 X
第1章 緒論 1
1.1 背景介紹 1
1.2 研究動機與目的 4
1.3 論文架構 6
第2章 文獻回顧 8
2.1影像幾何校正 8
2.1.1 保角轉換 9
2.1.2 仿射轉換 10
2.1.3 八參數轉換 11
2.2牆面紋理分析 13
第3章 研究方法及步驟 19
3.1研究方法綜述 19
3.2初始資料探討 21
3.2.1 CityGML LOD 1 積木式房屋模型 23
3.2.2 近景影像 25
3.2.3 通用紋理資料庫 29
3.3近景影像幾何校正 31
3.3.1 房屋角點在影像上坐標之計算 31
3.3.2 影像校正—八參數轉換 35
3.3.3 感興趣區域切割 37
3.4牆面影像分析—窗戶幾何 38
3.4.1 窗戶遮罩計算 39
3.4.2 牆面紋理樓層切割與各樓層相似度比對 41
3.4.3 窗戶遮罩優化 44
3.4.4 窗戶匹配 45
3.5牆面影像分析—牆面顏色 46
3.5.1 牆面顏色分群 47
3.5.2 通用紋理顏色匹配 50
3.6改良牆面通用紋理資料庫 53
第4章 實驗成果與分析 54
4.1研究區域介紹 54
4.2街景影像校正成果與探討 57
4.3 窗戶與植物遮罩計算 63
4.4 影像分析—窗戶幾何 66
4.5 影像分析—牆面顏色 69
4.6 擬真牆面通用紋理敷貼成果展示 72
第5章 總結與建議 80
5.1研究總結 80
5.2研究建議 82
參考文獻 84
參考文獻 陳正軒,「以視訊影像進行三維房屋模型實景紋理敷貼之研究」,國立中央大學,碩士論文,民國94年。

林后駿,「三維房屋模型實景紋理影像製作與敷貼之研究」,國立中央大學,碩士論文,民國94年。

陳品學,「影像修補技術於牆面紋理影像遮蔽去除之應用」,國立中央大學,碩士論文,民國98年。

蔡富安、陳良健,「三維數位城市之建置及應用」,國土資訊系統通訊,(73),18-30頁,民國98年。

李孟儒,「利用近景影像提高三維建物模型之細緻化等級」,國立中央大學,碩士論文,民國98年。

蔡富安、張智安、張桓、陳良健、陳杰宗,「多尺度三維數位房屋模型建置」,航測及遙測學刊,267-285頁,民國102年。

施凱倫,「利用測繪車影像萃取道路標誌重建細部道路模型」,國立中央大學,碩士論文,民國103年。

Ball, G. H., & Hall, D. J. (1965). ISODATA, a novel method of data analysis and pattern classification. Technical report NTIS AD 699616. Stanford Research Institute, Stanford, CA.

Biljecki, F., Stoter, J., Ledoux, H., Zlatanova, S., & Coltekin, A. (2015). Applications of 3D city models: State of the art review. ISPRS International Journal of Geo-Information, 4(4), pp. 2842-2889.

Chang, K., Tsai, F. (2016). Semi-automatic generic textures matching for effective city model visualization. In Proceedings of the International Symposium on Remote Sensing (ISRS), pp. 415-418.

Coggins, J.M. and Jain, A.K. (1985), A Spatial Filtering Approach to Texture Analysis, Pattern Recognition Letters, 3, pp. 195-203.

Dai, D., Riemenschneider, H., Schmitt, G., & Van Gool, L. (2013). Example-based facade texture synthesis. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), Sydney, Australia, pp. 1065-1072.

Despine, G., & Colleu, T. (2015). Adaptive Texture Synthesis for Large Scale City Modeling. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(5), pp. 155-162.

Debevec, P. E., Taylor, C. J., & Malik, J. (1996). Modeling and rendering architecture from photographs: A hybrid geometry-and image-based approach. In Proceedings of the 23rd annual conference on Computer graphics and interactive techniques, pp. 11-20.

Dollner, J., Baumann, K., & Buchholz, H. (2006). Virtual 3D city models as foundation of complex urban information spaces, pp. 107-112. na.

Frueh, C., Sammon, R., & Zakhor, A. (2004). Automated texture mapping of 3D city models with oblique aerial imagery. In Proceedings of the 2nd International Symposium 3D Data Processing, Visualization, and Transmission (3DPVT 2004).

Frueh, C., & Zakhor, A. (2003). Constructing 3D city models by merging ground-based and airborne views. In Proceedings of Computer vision and pattern recognition (CVPR).

Hughes, J. F., Van Dam, A., Foley, J. D., McGuire, M., Feiner, S. K., Sklar, D. F., & Akeley, K. (2014). Computer graphics: principles and practice: Pearson Education.

Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern recognition letters, 31(8), pp. 651-666.

Jang, S. W., Kim, G. Y., & Byun, S. (2014). Clustering-based pattern abnormality detection in distributed sensor networks. International Journal of Distributed Sensor Networks, 10(4), 438468.

Kolbe, T. H., Groger, G., & Plumer, L. (2005). CityGML: Interoperable access to 3D city models. In Proceedings of the first International Symposium on Geo-Information for Disaster, pp. 883-899.

Koffka, K. (2013). Principles of Gestalt psychology. Routledge.

Liebowitz, D., Criminisi, A., & Zisserman, A. (1999). Creating architectural models from images. In Proceedings of EuroGraphics, vol. 18.

Levinshtein, A., Stere, A., Kutulakos, K. N., Fleet, D. J., Dickinson, S. J., & Siddiqi, K. (2009). Turbopixels: Fast superpixels using geometric flows. IEEE transactions on pattern analysis and machine intelligence, 31(12), pp. 2290-2297.

Martinovi?, A., Mathias, M., Weissenberg, J., & Van Gool, L. (2012). A three-layered approach to facade parsing. In Proceedings of European conference on computer vision, pp. 416-429.

Mastin, A., Kepner, J., & Fisher, J. (2009). Automatic registration of LIDAR and optical images of urban scenes. Institute of Electrical and Electronics Engineers, pp. 2369-2646.

Otsu, N. (1979). A threshold selection method from gray-level histograms. IEEE transactions on systems, man, and cybernetics, 9(1), pp. 62-66.

Rupnik, E., Nex, F., & Remondino, F. (2014). Oblique multi-camera systems-orientation and dense matching issues. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(3), pp. 107-114.

Semple, J. G., & Kneebone, G. T. (1998). Algebraic projective geometry: Oxford University Press.

Szeliski, R., & Shum, H.-Y. (1997). Creating full view panoramic image mosaics and environment maps. In Proceedings of the 24th annual conference on Computer graphics and interactive techniques, pp. 251-258.

Taneja, A., Ballan, L., & Pollefeys, M. (2012). Registration of spherical panoramic images with cadastral 3d models. In Proceeding of 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2012 Second International Conference, pp. 479-486.

Teboul, O., Kokkinos, I., Simon, L., Koutsourakis, P., & Paragios, N. (2011). Shape grammar parsing via reinforcement learning. In Proceedings of Computer Vision and Pattern Recognition (CVPR).

Udayan, J. D., & Kim, H. (2018). Procedural Restoration of Texture and Restructuring Geometry From Facade Image. IEEE Access, 6, pp. 2645-2653.

Wang, L., & He, D. (1990). A new statistical approach for texture analysis. Photogrammetric Engineering and Remote Sensing, 56(1), pp. 61-66.

Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing, 13(4), pp. 600-612.

Wolf, P. R., & Dewitt, B. A. (2000). Elements of photogrammetry: with applications in GIS: McGraw-Hill New York.

Xiao, J., Gerke, M., & Vosselman, G. (2012). Building extraction from oblique airborne imagery based on robust facade detection. ISPRS Journal of Photogrammetry and Remote Sensing, 68, pp. 56-68.

Zujovic, J., Pappas, T. N., & Neuhoff, D. L. (2013). Structural texture similarity metrics for image analysis and retrieval. IEEE Transactions on Image Processing, 22(7), pp. 2545-2558.
指導教授 蔡富安(Fuan Tsai) 審核日期 2018-8-23
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