Abstract
Abstract. Low cost imaging and positioning sensors are opening new frontiers for applications in near real-time Photogrammetry. Omnidirectional cameras acquiring images with 360° coverage, when combined with information coming from GNSS (Global Navigation Satellite Systems) and IMU (Inertial Measurement Unit), can efficiently estimate orientation and object space structure. However, several challenges remain in the use of low-cost sensors and image observations acquired by sensors with non-perspective inner geometry. The accuracy of the measurement using low-cost sensors is affected by different sources of errors and sensor stability. Microelectromechanical systems (MEMS) present a large gap between predicted and actual accuracy. This work presents a study on the performance of an integrated sensor orientation approach to estimate sensor orientation and 3D sparse point cloud, using an incremental bundle adjustment strategy and data coming from a low-cost portable mobile terrestrial system composed by off-theshelf navigation systems and a poly-dioptric system (Ricoh Theta S). Experiments were performed in an outdoor area (sidewalk), achieving a trajectory positional accuracy of 0.33 m and a meter level 3D reconstruction.
Highlights
The advancements in the photogrammetric data processing and the increasing number of low-cost and lightweight navigation (MEMS) and imaging sensors, available in the market have encouraged the development of new integrated sensor orientation (ISO) approaches
The ΔZ value was computed considering the height of ground control points (GCP) in the begging of the trajectory aligned with the camera center position, which enable a better estimation of the initial 3D ground coordinates
This work presented a feasibility study of an incremental bundle adjustment methodology for real-time orientation and mapping, based on ISO approach and using data coming from a low-cost and lightweight portable mobile terrestrial system (PMTS) acquired in an outdoor test area
Summary
The advancements in the photogrammetric data processing and the increasing number of low-cost and lightweight navigation (MEMS) and imaging sensors, available in the market have encouraged the development of new integrated sensor orientation (ISO) approaches. These sensor technologies have opened many possibilities for real-time Photogrammetry considering several sets of observations from different sources. Omnidirectional systems are an attractive alternative due to large field of view around the sensor, which allows more features to be tracked in a single image shot Using these new navigation and imaging sensors requires adaptations in the photogrammetric processes to support applications in CRP. This paper presents an ISO approach to estimate sensor orientation and a sparse 3D point cloud from data acquired by a low-cost portable mobile terrestrial system (PMTS), using an incremental bundle adjustment strategy consistent with the fisheye lens geometry
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