Abstract. The evolution of mapping platforms has followed a consistent pattern: professional instruments are complemented by consumer devices that trade precision for scalability. Unmanned aerial systems transformed aerial photogrammetry by making it accessible beyond traditional aircraft, and smartphones, especially when equipped with high accuracy GNSS positioning, have demonstrated viable terrestrial mapping. This paper extends that progression to vehicle-based mapping by presenting SurveyXR, a web-based calibration and georeferencing framework that converts dashcam video from a GNSS-equipped vehicle into georeferenced imagery suitable for Structure-from-Motion (SfM) processing. By providing accurate per-frame exterior orientation parameters, the system enables direct georeferencing of the SfM output, eliminating the need for ground control points in the photogrammetric workflow. The pipeline implements checkerboard-based intrinsic calibration with automated quality diagnostics, Perspective-n-Point exterior orientation solving with automatic boresight detection, GNSS-synchronized frame extraction, and lever arm correction between the GNSS antenna and each camera. All computation runs in a browser or lightweight cloud backend, requiring no local software installation. The framework was evaluated on a 2026 Tesla Model Y equipped with a roof-mounted Emlid Reach RS4 Pro PPK GNSS receiver on the Ohio State University campus. Georeferencing accuracy was assessed against 71 independently surveyed RTK check points in two configurations: direct georeferencing only (no ground control) and GCP-constrained bundle adjustment. The paper documents the calibration methodology, time synchronization model, error budget analysis, and quantitative accuracy assessment.
R. Tamimi, C. Toth· The International Archives o...· 0 citations
Abstract. Professional mobile mapping systems achieve centimeter-level accuracy through the tight integration of navigation-grade IMUs, survey-grade GNSS, and calibrated laser scanners. This paper assesses the relative and absolute accuracy of a vehicle-mounted test platform that combines a NovAtel SPAN tightly coupled GNSS/IMU with a mid-grade Velodyne VLP-16 LiDAR, evaluated along a 1.2 km test loop on The Ohio State University campus. The mobile-cloud georeferencing is driven entirely by the SPAN-processed GNSS/IMU trajectory, post-processed in NovAtel Inertial Explorer; three additional survey-grade PPK GNSS receivers are processed independently and serve as cross-checks on the trajectory. Direct georeferencing is performed in the standard ECEF formulation with per-point trajectory interpolation. An independent reference point cloud of the same area is acquired with a Leica RTC360 terrestrial laser scanner, registered and tied down to GNSS-derived ground control so that the TLS cloud carries an independent absolute geodetic datum. Absolute accuracy is then evaluated directly: identifiable features on building façades are coordinated independently in each cloud, and the coordinate differences between the mobile-cloud and TLS positions of the same features quantify the absolute georeferencing error of the directly georeferenced mobile cloud. Relative accuracy is evaluated separately from the internal geometry of each cloud: structure dimensions, inter-feature distances, and inter-feature angles are measured in the mobile cloud and in the TLS and compared, isolating the shape-preservation performance of the platform from any constant offset between the two reference frames. An auxiliary SHARE SLAM S20 handheld scanner mounted on the same vehicle is described as supplementary platform context; its data is not used in the accuracy assessment due to unreliable GNSS/IMU/SLAM integration at vehicle speeds.
R. Tamimi, Baris Süleymanoğlu, A. Elashry et al.· The International Archives o...· 0 citations
BEV-LOC is presented, a lightweight and real-time cross-view geolocalization method that employs Bird’s Eye View encoder that learns to transform 360-degree multi-PV images into a local high-definition (HD) BEV map and is performed using Intersection Over Union (IoU)-based template matching with an offline global map.
J. Kwag, C. Toth, Alper Yilmaz· The International Archives o...· 0 citations
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