There is extensive research on passengers mobility estimated position. Among these approaches, Simultaneous Localization And Mapping (SLAM) is one of the most frequent methods that exponentially increase the computational complexity. To overcome this problem, we propose a method based on augmented reality that reduces the computational complexity by using less computing power. With this method, each target image is characterized by three dimensions: position, content and size. The passenger is equipped with a smartphone that captures images, processes and compares them with a database to overlay the virtual 3D elements with the real world.