模型合成就如同貼圖合成一般，同樣是給定一個作為輸入的範例，然後系統就會按照範例上的一些特徵生成更大尺寸的結果出來。現在模型合成的方法也已經被提出了的許多，但都是使用範例上的特徵資料近乎無所限制地在空間中隨意生成，如此我們很難得到一個特定的外型或是使用這些特徵生成出一個我們想要的外型出來。

在這篇論文裡，我們所要處理的模型都是建築物的模型，我們把要合成的特徵來源改成了某一模型的材質貼圖上，並且由這個材質上面的結構得出了結構之間的位置關係，我們生成了新的建築模型且近似於指定建築之點雲資料的外觀形狀。

我們提出了一個新的逼近方法去產生近似點雲資料的模型，先以很多個相同尺寸的細胞即小方塊去堆積出點雲的外觀形狀，然後從一個過擬合的狀態不斷的進行表面雕刻得到逼近的模型結果；然後再從對稱性去分析建築物影像上的結構，然後將其自動貼到新產生出來的模型上。

Similar to texture synthesis, model synthesis is the process of synthesizing 3D models by an input 3D model. The methods for model synthesis have been proposed much many. Because the model generated by model synthesis are often extended them self without limitation, it is hard to get specified appearance of the synthesized model.

In this thesis, the model which we will process is the building’s model. The feature of synthesis comes from a texture material of a building’s model, and we extract the positional relationship from the material’s structure, generating a new building model with the specified building’s appearance.

We propose a new approximation method which uses several cells with same size to pile a model with similar appearance of the point cloud data. In order to approximate the detail of the point cloud, we make the generated model overfitting, and then carving it with specific conditions iteratively. Finally, we use symmetry to analyze the structure from the image of a building, and then we could texture them on the new generated model automatically.

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