輪廓法(Shape from silhouette)是一種簡單快速重建三維模型的技術，主要是透過一系列不同視角的物件二維影像來建立三維模型，由於僅利用影像外型輪廓資訊計算出三維模型在空間中的點雲資料，往往會因為影像內部資訊不足，得到不存在於實際物件上的頂點，導致在建立模型表面時產生了假面(Artifact)，其中又以無法得到資訊的模型底部最為嚴重，造成三維模型整體外觀與實際物件產生差異。本研究主要目的為發展一套基於輪廓法之三維模型品質改善的演算法，包含了三個主要流程，首先，透過在網格原始多邊形邊界與內部插入新頂點來建構三角網格，提升原始模型三角網格品質，接著利用拉普拉斯平滑化來去除模型上的假面同時也可以提升模型表面品質，而為了避免過度平滑導致模型失真，透過利用原始物件影像輪廓與模型投影輪廓的比對來保持模型的外型與特徵，使改善後的模型能更加接近實際物件。本研究最後將會以三個實際案例來驗證此演算法的正確性。;The shape from silhouette (SFS) method is a simple and fast technique for reconstructing the three-dimensional (3D) model of an object from a series of two-dimensional images. It only employs the silhouettes of the object images to generate a set of cloud points describing the object surface. However, the problem is that it may result in some vertices that do not really exist on the object. Hence the resulting 3D model may have artifacts, indicating that the shape of the reconstructed model is different from that of the real object. The purpose of this study is to develop a method for improving quality of the SFS model. There are mainly three algorithms in the proposed method. First, a new triangulation algorithm is proposed for improving the quality of the triangular model obtained from the cloud points. The proposed algorithm mainly inserts new vertices for improving the occurrence of long-and-narrow triangles that might occur in the original method. Second, a Laplacian smoothing algorithm is employed for removing artifacts and improving the smoothness of the triangular meshes. Finally, to maintain the accuracy of the silhouette of the 3D model projected onto each image, an error controlling algorithm by comparing both silhouettes of the projected model and the image is proposed. The second and third algorithms are formulated as an iterative procedure for optimizing the 3D model. The final 3D model would be closer to the shape of the real object after the above-mentioned optimization process. Three object examples are employed for demonstrating the entire procedures and the feasibility of the proposed method.
