Real-world three-dimensional reconstruction is a project of long-standing interest in global computer vision. Many tools have emerged these past years to accurately perceive the surrounding world either through active sensors or through passive algorithmic methods. With the advent and popularization of augmented reality on smartphones, new visualization issues have emerged concerning the virtual experience. Especially a 3D model seems to be essential to provide more realistic AR effects including consistency of occlusion, shadow mapping or even collision between virtual objects and real environment. However, due to the huge computation of most of current approaches, most of these algorithms are working on a computer desktop or high-end smartphones. Indeed, the reconstruction scale is rapidly limited by the complexity of both computation and memory. Therefore, our study aims to find a relevant method to process real time reconstruction of close-range outdoor scenes such as cultural heritage or underground infrastructures in real time locally on a smartphone.