A Triangle Mesh Reconstruction Method Taking into Account Silhouette Images

In this paper, we propose a novel approach to reconstruct triangle meshes from point sets by taking the silhouette of the target object into consideration. Recently, many approaches have been proposed for complete 3D reconstruction of moving objects. For example, motion capture techniques are used to acquire 3D data of human motion. However, it needs to attach markers onto the joints, which results in limiting the capturing environments and the number of data that can be acquired. In contrast, to obtain dense data of 3D object, multi-view stereo scanning system is one of the powerful methods. It utilize images taken by several directions and enables to reconstruct 3D dense point sets by using Epipolar geometry. However, it is still challenging problem to reconstruct 3D triangle mesh from the 3D point sets due to the abundant points originated by mismatched points between images. We propose a novel approach to obtain more accurate triangle mesh reconstruction method than the previous one. We take advantage of silhouette images acquired in the process of reconstructing 3D point sets that result in removing noises and compensating holes. Finally, we demonstrate that the proposed method can generate the details of the surface, where the previous method loses from a small number of points.