Robust multi-view reconstruction from quasi-dense point cloud and poisson surface mesh

A novel method for generating a reliable initial surface mesh of the interested scene from a quasi-dense point cloud is presented in this article. Given multiple images taken from different points of view, a robust quasi-dense point cloud is acquired by accumulative triangulation of the potentially matched feature points. In our proposed method, the feature points are detected with Harris-corner and SIFT detectors. SIFT and DAISY descriptors are used to describe the neighboring environment of the detected features and provide efficient matching possibilities. The proposed method can be parallelized almost at each phase, which makes it suitable for image datasets of different sizes. The accuracy of the proposed method is evaluated quantitatively and qualitatively on different types and sizes of image datasets.