Real-time Vehicle Localization and Tracking Using Monocular Panomorph Panoramic Vision

This paper presents a feasibility analysis of the ORB-SLAM [1] for real-time vehicle localization and tracking using a monocular visual camera providing 360° panoramic views. This method described in [1] was initially designed and developed for conventional cameras, making use of a method for detection and tracking visual features and estimating the camera trajectory while reconstructing the environment. The accuracy of the tracking depends on the ability of this method to robustly detect and match sufficient visual features. This work aims to extend this method to large monocular round views using fish-eye-like cameras allowing an increase of visual features with the aim of improving localization robustness. The main challenge in using a standard fish-eye camera for generating panoramic views is the reduction of visual performance due to a potential higher distortion and lower spatial resolution compared to that using a standard camera lens. The objective of this research is to perform a feasibility analysis of a method combining a camera equipped with a panomorph lens to generate real-time panoramic views at minimal distortion and ORB-SLAM to robustly detect and track visual features for real-time camera localization and tracking. A quantitative evaluation is performed on a vehicle driving in an outdoor natural scene with the monocular panomorph camera mounted on-front and without any other additional sensors. The results with analysis and a concluding summary are included as well.