This paper introduces a structure from motion (SfM)-based surface reconstruction method for images including weak textures and structures. In SfM, the quality of the determination of homologous points between images plays a key role in terms of reconstruction performances. However, classical feature matching-based methods as integrated in the state-of-the-art SfM algorithms are often inoperative for images with weak structures and textures. This contribution describes a dense optical flow-based solution enabling the point correspondence determination in such scenes. The accuracy and robustness of the proposed method were validated using results obtained for a phantom with known dimensions and with real medical data, respectively. Complex internal stomach wall surfaces were constructed using gastroscopic images.