Image-Based Camera Localization Algorithm for Smartphone Cameras Based on Reference Objects

Navigating an individual in both outdoor and indoor environments would provide great facilities for the community. Image-based approaches are more affordable and feasible in comparison to the high cost of sensor devices and unavailability of guiding by GPS in indoor systems. Thus, we develop our system using cameras owing to their easy availability and accessibility. Primarily, detecting the location of personnel is needed to orientate a human. However, determining camera localization is a challenging task on the computer vision field. Therefore, in this study, a novel approach is proposed to address the problem using panoramic image sequences. We apply the scale invariant future transform for detecting corresponding points, and based on these points, a reference object is considered. The Levenberg-Marquardt optimization method is utilized to minimize reprojection errors for a given pair of images. As a better alternative to traditional methods, which apply the known surface of a reference object, our formulation rests on the scale ambiguity in different coordinate systems. Experiments are performed on Herz-Jesus-P8, Fountain-P11, and Fountain-P25 datasets to evaluate our dataset and compare our proposal with respect to prior works. We believe our proposal comparatively outperforms previous works indicating lower error rate in wide baselines between camera pairs.