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研究生:柯奇君
研究生(外文):Chi-chun Ko
論文名稱:以剪影輪廓為基礎的三維特徵與模型檢索
論文名稱(外文):Silhouette Based Feature Representation and Matching for 3D Model Retrieval
指導教授:杜維昌杜維昌引用關係
指導教授(外文):Wei-Chang Du
學位類別:碩士
校院名稱:義守大學
系所名稱:資訊工程學系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
語文別:中文
論文頁數:55
中文關鍵詞:外形輪廓模型剪影資料檢索三維模型
外文關鍵詞:model silhouette3D modeldata retrievalshape contour.
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  • 下載下載:27
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隨著顯像技術的日益提升,三維模型在網路上有如雨後春筍般的大量出現,為了進一步有效作管理,三維模型檢索的相關技術也日益顯得重要。在此一研究中,將以外形剪影輪廓為基礎,探討三維模型的特徵表達與資料檢索。我們主要透過傅立葉描述子來表達具備平移、旋轉和縮放不變量的剪影特徵,並以多階層輪廓來描述模型的拓樸性關係。一般來說,在空間中可用任意視覺角度來得到三維模型的剪影資料,因而適當的量化與剪影數的精簡是提升檢索必要的過程。為了讓不同複雜度的模型取得適量的剪影集合,分析剪影的相似度以決定記錄的張數,然後以這些剪影集合來描述三維模型的特徵。我們以普林斯頓大學三維模型資料庫為例,使用者可以手繪輪廓或模型範例等查詢介面在資料庫中進行檢索,以驗證其執行成效。
Along with the rapid development of rendering technology, more and more 3D geometric models are available on the Web. For a more efficient management on this data, the 3D model retrieval related technologies have become an important issue. In the thesis, our objective is to develop a reliable feature representation and data retrieval of 3D models based on all possible silhouettes of 3D models. We describe the model silhouette mainly by using Fourier descriptors to get an invariant feature of translation, scaling and rotation, and then use a tree hierarchy containing the multi-level contour structure to describe the topological properties. In order to reduce the number of stored silhouettes, so as to promote query performance, performing a proper simplification for all silhouettes is an essential process. For such a reason, an adaptive silhouette quantization is used by analyzing the similarity among each other. Using a practical 3D database as our tested example, we have implemented a 3D retrieval system, in which user can query either by 2D user-drawn sketches or by 3D model example, to demonstrate the effectiveness of proposed methods.
摘 要 I
Chapter 1 簡介
Chapter 2 三維模型檢索技術之相關研究
2.1以主軸為基礎的相似度比對
2.1.1方位校正
2.1.2以主軸外形分佈為基礎的相似度比對
2.1.3以主軸投影為基礎的相似度比對
2.2以外形分佈為基礎的相似度比對
2.3以實心模型為基礎的相似度比對
2.4以拓樸為基礎的相似度比對
Chapter 3 以剪影輪廓為基礎的三維特徵與模型檢索方法
3.2輪廓的記錄
3.3輪廓特徵表示方法
3.4剪影的比對
3.5關鍵剪影
3.5.1 k-means剪影分群方法
3.5.2以差異量的方式決定關鍵剪影
3.5.3關鍵剪影個數的決定
3.6模型的檢索方式
Chapter 4 實驗結果
4.1傅立葉轉換分析
4.2階層式輪廓比對的效果
4.2.1多層輪廓之剪影自我比對的效果
4.2.2有無多層輪廓之剪影混合比對的效果
4.3關鍵剪影數目的分析
4.4以輸入模型進行檢索
4.5以手繪方式進行檢索
Chapter 5 結論
參考文獻
[1]Johan W.H. Tangelder and Remco C. Veltkamp, “A Survey of Content Based 3D Shape Retrieval Methods,” Proceedings of the Shape Modeling International, 2004.
[2]Ding-Yun Chen, Xiao-Pei Tian, Yu-Te Shen and Ming Ouhyoung, “On Visual Similarity Based 3D Model Retrieval,” The Eurographics Association and Blackwell Publishers, 2003.
[3]Tarik Filali Ansary, Jean-Philippe Vandeborre, Said Mahmoudi and Mohamed Daoudi, “A Bayesian Framework for 3D Models Retrieval Based on Characteristic Views,” Proceedings of the 2nd International Symposium on 3D Data Processing, Visualization, and Transmission, 2004.
[4]Thomas Funkhouser, Patrick Min, Michael Kazhdan, Joyce Chen, Alex Halderman, and David Dobkin, “A Search Engine for 3D Models,” ACM Transactions on Graphics, vol. 22, no. 1, pp. 83-105, January 2003.
[5]Ryutarou Ohbuchi, Takahiro Minamitani and Tsuyoshi Takei, “Shape-Similarity Search of 3D Models by using Enhanced Shape Functions,” Theory and Practice of Computer Graphics, Birmingham, U.K, pp. 97-104, June 2003.
[6]Yoshihiro Okada, “3D Model Database System by Hand Sketch Query,” IEEE, vol. 1, pp. 889-892, 2002.
[7]Ryutarou Ohbuchi, Tomo Otagiri, Masatoshi Ibato and Tsuyoshi Takei, “Shape-Similarity Search of Three-Dimensional Models Using Parameterized Statistics,” Proceedings of the Pacific Graphics, Beijing, China, October 9-11, 2002.
[8]Cha Zhang and Tsuhan Chen, “Efficient Feature Extraction For 2d/3d Objects In Mesh Representation,” IEEE International Conference on Image Processing, Oct. 2001.
[9]Yinan Zhou and Zhiyong Huang, “Decomposing Polygon Meshes by Means of Critical Points,” Proceedings of the 10th International Multimedia Modeling Conference, 2004.
[10]Dengsheng Zhang and Guojun Lu, “A Comparative Study on Shape Retrieval Using Fourier Descriptors with Different Shape Signatures,” International Conference on Intelligent Multimedia and Distance Education, pp. 1-9, 2001.
[11]Xiaoqian XU, D.J. LEE, “Curve Matching for Spine X-ray Image Retrieval using Dynamic Programming,” SPIE Medical Imaging, Picture Archive and Communication Systems (PACS) and Imaging Informatics, vol. 5748-47, San Diego, CA, USA, February 12-17, 2005.
[12]Michael Kazhdan, and Thomas Funkhouser, “Harmonic 3D Shape Matching,” SIGGRAPH 2002 Technical Sketches, pp. 191, July, 2002.
[13]Sagi Katz and Ayellet Tal, “Hierarchical Mesh Decomposition using Fuzzy Clustering and Cuts,” ACM Transactions on Graphics, vol. 22, Issue 3, July 2003.
[14]Jurgen Assfalg, Alberto Del Bimbo and Pietro Pala, “Spin images for retrieval of 3D objects by local and global similarity,” Proceedings of the 17th International Conference on Pattern Recognition, 2004.
[15]H. Sundar, D. Silver, N. Gagvani and S. Dickinson, “Skeleton Based Shape Matching and Retrieval,” Proceedings of the Shape Modeling International, 2003.
[16]Princeton University, Princeton Shape Retrieval and Analysis Group, 3D Models Search Engine, http://shape.cs.princeton.edu/search.html.
[17]P. Min, A. Halderman, M. Kazhdan and T. Funkhouser, “Early Experiences with a 3D Model Search Engine,” Web3D Symposium, pp. 7-18, March 2003.
[18]Takeo Igarashi, Satoshi Matsuoka and Hidehiko Tanaka, “Teddy: A sketching interface for 3D freeform design,” Proceedings of SIGGRAPH 1999, pp. 409-416, Los Angeles, CA, August 1999.
[19]R. Osada, T. Funkhouser, B. Chazelle and D. Dobkin, “Matching 3D Models with Shape Distributions,” Int. Conf. on Shape Modeling and Applications (SMI 2001), pp. 154-166, 2001.
[20]Meng Yu, Indriyati Atmosukarto, Wee Kheng Leow, Zhiyong Huang and Rong Xu, “3D Model Retrieval With Morphing-Based Geometric and Topological Feature Maps,” Computer Vision and Pattern Recognition, pp. 656-661, 2003.
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