V-Slam-AIded Photogrammetry to Process Fisheye Multi-Camera Systems Sequences

Abstract. The advent of mobile mapping systems (MMSs) and computer vision algorithms has enriched a wide range of navigation and mapping tasks such as localisation, 3D motion estimation and 3D mapping. This study focuses on Visual Simultaneous Localisation and Mapping (V-SLAM) in the context of two in-houses MMSs: Ant3D, a patented five-fisheye multi-camera rig and GeoRizon, a high-resolution stereo fisheye rig. The aim is to leverage V-SLAM to enhance the systems performance in near-real-time and non-real-time 3D reconstruction applications. The research investigates both Monocular and Stereo V-SLAM applied to both MMSs and tackles the challenge of combining the V-SLAM estimated trajectory of one or a pair of cameras with known multi-camera relative orientation. We propose a state-of-the-art code that serves as a flexible and extensible platform for MMSs image acquisition and processing, along with an adapted version of the well-established ORB-SLAM3.0. Evaluation is performed in a cultural heritage challenging setup: the Minguzzi spiral staircase in the Duomo di Milano Cathedral. Performed tests highlight that introducing V-SLAM trajectories as well as pre-calibrated interior orientation and multi-camera constraints improve speed, applicability and accuracy of 3D surveys.