3D versus 2D based indoor image matching analysis on images from low cost mobile devices

Because of the increasing popularity of camera-equipped mobile devices, image matching techniques offer a potential solution for indoor localisation problems. However, image matching is challenging indoors because different indoor locations can look very similar. In this paper, we compare two image-based localisation approaches on realistic datasets that include images from cameras of varying quality. The first approach is based on 3D matching and the second on 2D matching. The comparison shows that 3D image matching crucially depends upon on the quality of the camera and its correct image matching accuracy ranges from 62-92% depending on the dataset. In contrast, the matching accuracy of 2D image matching is consistent across all cameras and ranges from 80-95%. In terms of computational efficiency, the 2D method is five times more efficient, but both methods are fast enough for many applications. We further investigate the performance of the 2D approach on four realistic indoor datasets with 50 indoor locations, such as corridors, halls, atrium or offices. Four out of five test sets have correct acceptance greater than 85% showing that image-based methods are viable for indoor localisation applications.