Conference Agenda

The presence of refraction-induced systematic errors has always been a cause of concern in the field of underwater photogrammetry.

This work extends previous studies from the authors with new simulations specifically aimed at practical applications underwater using popular sensor devices and configurations, such as GoPro action cameras fitted with standard flat port housing that are very common among marine ecologists and archaeologists.

We aim at investigating whether approaches used by regular photogrammetry above water can be applied underwater without a significant accuracy loss for the application of interest.

Due to the complexity of collecting ground truth data, simulations are used. We utilize the POSER framework (https://github.com/GEOSS-UNISS/POSER) developed within the 2024 ISPRS Education and Capacity Building Initiatives (ECBI).

We investigate the benefits and cons of the refractive vs the implicit modelling approaches with respect to estimability of camera calibration (refractive) parameters, need for pre-calibration setups with approaches from literature, availability of ground control points, and assessing the accuracy of both approaches against ground truth simulated data.

The accuracy is reported as discrepancies in the reconstructed 3D models, exterior orientation and camera calibration parameters.

Reconstructing the water surface in refractive domains such as rivers and lakes is challenging, since light bending at the air-water interface alters the apparent geometry and breaks the straight-ray assumption of conventional image-based 3D reconstruction. Accurate water surface models are therefore a key prerequisite for many refraction-aware applications. This contribution investigates the potential of three passive image-based methods, Structure from Motion (SfM), Multi-View Stereo (MVS), and Monocular Depth Estimation (MDE), to derive a geometrically consistent water surface model from UAV imagery of the Pielach River study site in Austria. The dataset represents a demanding scenario with clear, fast-flowing water and low texture, which causes strong refraction and poor feature stability. Quantitative comparisons against LiDAR-derived reference surfaces show that SfM yields sparse and inconsistent points, MVS reconstructs the riverbed instead of the water surface, and MDE exhibits scale and offset inconsistencies despite explicit calibration using SfM reprojections. Completeness remains below 45 % for all methods with mean vertical deviations in the decimetre-to-metre range. The results indicate that current image-based approaches are insufficient for reliable water-surface reconstruction in such settings, reinforcing the need for an explicitly derived surface model as input to refraction-aware modeling, for example in bathymetric reconstruction and future refractive neural rendering methods, rather than relying on implicitly learned water surfaces.

This article studies the complementary usage of RTI and SfM-MVS visual inspection (visual testing) of welds under water. Two compact low-cost lighting domes of different designs were developed and deployed with a monochromatic camera at close range.

The lighting domes generate homogenous and direct illumination, respectively, tailoring the requirements of SfM and RTI. The camera is housed in a cylindrical tube, equipped with a dome port interface.

The 3D reconstruction in combination with RTI models could augment existing testing strategies and provide digital, gapless documentation. Experiments were conducted in laboratory in air, clear and turbid water questioning were the capabilities and limits are for given setup with respect to visual testing of welds.

Under the correct lightning, in air the techniques perform on a high accuracy level and are well suited for inspecting welds digital and interactively. Underwater the results differ in dependence of the degree of turbidity and prove to be sensitive for configurational parameters leaving space for improvements of acquisition and processing workflows. However, even in turbid water the 3D reconstructions and RTI models could be calculated enabling novel possibilities for weld inspection.

A novel hand–eye calibration method for ground-observing mobile robots is proposed. While cameras on mobile robots are common, they are rarely used for ground-observing measurement tasks. Laser trackers are increasingly used in robotics for precise localization. A referencing plate is designed to combine the two measurement modalities of laser-tracker 3D metrology and camera-based 2D imaging. It incorporates reflector nests for pose acquisition using a laser tracker and a camera calibration target that is observed by the robot-mounted camera. The procedure comprises estimating the plate pose, the plate–-camera pose, and the robot pose, followed by computing the robot–-camera transformation. Experiments indicate sub-millimeter repeatability.

Early detection of structural issues is crucial for timely maintenance and extending bridge lifespans. Conventional visual inspections alone are not sufficient for the vast number of structures, highlighting the need for intelligent, real-time monitoring systems. The studies presented here were conducted as part of the DFG priority programme SPP100+ in collaboration with the IDA-KI project. In addition to conventional civil engineering sensors, the 45-meter-long openLAB research bridge, a three-span prestressed concrete structure, was equipped with target fields for photogrammetric measurements. During controlled load tests, in which a motorized load vehicle passes over the bridge, a high-resolution camera captures image sequences of the measurement fields. The photogrammetric workflow involved camera calibration, image sequence acquisition, and precise 3D coordinate determination using coded targets. Displacement values in the range of several millimeters were calculated frame-by-frame. Results from a typical load cycle showed initial upward deflection followed by downward movement, corresponding to the load vehicle’s passage. This approach demonstrates the potential of photogrammetry for accurate, non-contact deformation monitoring, supporting the development of digital twins and advanced structural health monitoring systems for bridges.

Body donation remains critically important for anatomical science, allowing examination of biological structures with three-dimensional (3D) context. However, body donors (cadavers) are a time-limited resource and the scarcity of body donors has prompted an interest in digital body preservation. Multiple imaging techniques (e.g., conventional photogrammetry[CPG], stereophotogrammetry[SPG] and computed tomography[3DCT]) can capture the 3D characteristics of a specimen indefinitely. Digital anatomical records provide an opportunity to measure anatomical structures in the absence of the physical specimen. In 2022, the face of a preserved body donor was digitally reconstructed using CPG and 3DCT. 28 months later, a repeat survey was performed using SPG and a series of facial landmarks were directly measured. The accuracy and stability of facial soft-tissues over time were measured using point-to-point and cloud-to-mesh techniques. The results show that anatomical models produced by 3DCT and CPG produce similar facial measurements to those acquired by SPG and direct measurement at later timepoints. These data indicate that chemical fixation adequately stabilises facial anatomy over time, each sensor can be used interchangeably for facial measurement and models can be co-registered with minimal discrepancy.

Speech is a highly complex and multidimensional process, requiring precise coordination of muscular actions within the vocal tract. Disruptions or delays in speech motor control often lead to speech impairments. Recent advancements in markerless facial tracking technology enable the collection of objective measurements to assess these impairments. To obtain such photogrammetric measurements, a multi-camera network is employed, making accurate camera calibration essential. This paper examines the constraints applied during the calibration process. Two adjustment strategies were evaluated. The first, Independent Adjustment (IDP), performs self-calibration for each camera without introducing constraints. The second, Combined Adjustment (CMB), incorporates object space constraints by ensuring that object point locations observed from all cameras remain consistent. Given the cameras’ narrow fields of view, both IDP and CMB were tested with additional constraints related to the principal point offset. Each adjustment was executed under two conditions: fixing the principal point offset to zero or estimating it as part of the calibration. Results indicate that the choice of adjustment significantly affects the interior orientation parameters (IOPs). IDP with the principal point offset fixed to zero produced the most accurate outcomes. However, variations in IOPs had no meaningful impact on object space coordinates. These findings suggest that the simplest approach—IDP with the principal point offset fixed to zero—offers reliable calibration for multi-camera systems used in speech assessment. This streamlined method can be adopted in future applications to enhance efficiency without compromising accuracy.