Abstract. For optical 3D measurements in close-range and UAV applications, the modelling of interior orientation is of superior importance in order to subsequently allow for high precision and accuracy in geometric 3D reconstruction. Nowadays, modern camera systems are often used for optical 3D measurements due to UAV payloads and economic purposes. They are constructed of aspheric and spherical lens combinations and include image pre-processing like low-pass filtering or internal distortion corrections that may lead to effects in image space not being considered with the standard interior orientation models. With a variety of structure-from-motion (SfM) data sets, four typical systematic patterns of residuals could be observed. These investigations focus on the evaluation of interior orientation modelling with respect to minimising systematics given in image space after bundle adjustment. The influences are evaluated with respect to interior and exterior orientation parameter changes and their correlations as well as the impact in object space. With the variety of data sets, camera/lens/platform configurations and pre-processing influences, these investigations indicate a number of different behaviours. Some specific advices in the usage of extended interior orientation models, like Fourier series, could be derived for a selection of the data sets. Significant reductions of image space systematics are achieved. Even though increasing standard deviations and correlations for the interior orientation parameters are a consequence, improvements in object space precision and image space reliability could be reached.

Camera calibration via bundle adjustment is a well-established standard procedure in single-medium photogrammetry. When using standard software and applying the collinearity equations in multimedia photogrammetry, the effects of refractive interfaces are compensated in an implicit form, hence by the usual parameters of interior orientation. This contribution analyses different calibration strategies for planar bundle-invariant interfaces. To evaluate the effects of implicitly modelling the refractive effects within bundle adjustment, synthetic error-free datasets are simulated. The behaviour of interior, exterior, and relative orientation parameters is analysed using synthetic datasets free of underwater imaging effects. A shift of the camera positions of 0.2% of the acquisition distance along the optical axis can be observed. The relative orientation of a stereo camera shows systematic effects when the angle of convergence varies. The stereo baseline increases by 1% at 25° convergence. Furthermore, the interface is set up at different distances to the camera. When the interface is at 50% distance assuming a parallel camera setup, the stereo baseline also increases by 1%. It becomes clear that in most cases the implicit modelling is not suitable for multimedia photogrammetry due to geometrical errors (scaling) and absolute positioning errors. Explicit modelling of the refractive interfaces is implemented into a bundle adjustment and is also used to analyse calibration parameters and deviations in object space. Real experiments show that it is difficult to separate the effects of implicit modelling, since other effects, such as poor image measurements, affect the final result. However, trends can be seen, and deviations are quantified.

Understanding and considering refraction effects are important parts of the demanding task of multimedia photogrammetry, especially with planar interfaces, so-called ”flat ports”. Yet, it remains challenging to determine reliable calibration results that are both quickly acquired and physically interpretable. In this contribution, a novel object-based optimization algorithm, relying on ray tracing methods, is introduced. It enables calibrating physical parameters of all involved refractive properties with reduced computational effort, compared to other standard algorithms in ray tracing. We show that this solution produces equally accurate results as other ray tracing approaches while improving processing speed by a factor of approximately ten and providing a statistical metric in object space. Furthermore, we show in a laboratory investigation that explicit calibration of refractive properties is crucial even with orthogonally aligned bundle-invariant interfaces for highest accuracy, as accuracy in object space is decreased by about 10% with implicit calibration. With deviation from orthogonality by about ten degrees this decreases even further to almost no useful results and accuracy loss of more than 50% compared to explicit calibration results.

<p><strong>Abstract.</strong> In multimedia photogrammetry, multi-camera systems often provide scale by a calibrated relative orientation. Camera calibration via bundle adjustment is a well-established standard procedure in single-medium photogrammetry. When using standard software and applying the collinearity equations in multimedia photogrammetry, the refractive interfaces are modelled in an implicit form. This contribution analyses different calibration strategies for bundle-invariant interfaces. To evaluate the effects of implicitly modelling the refractive effects within a bundle adjustment, synthetic datasets are simulated. Contrary to many publications, systematic effects of the exterior orientations can be verified with simulated data. The behaviour of interior, exterior and relative orientation parameters is analysed using error-free synthetic datasets. The relative orientation of a stereo camera shows systematic effects, when the angle of convergence varies and when the synthetic interface is set up at different distances to the camera. It becomes clear, that in most cases the implicit modelling is not suitable for multimedia photogrammetry. An explicit modelling of the refractive interfaces is implemented into a bundle adjustment. This strict model is analysed and compared with the implicit form regarding systematic effects in orientation parameters as well as errors in object space. In a real experiment, the discrepancies between the implicit form using standard software and the explicit modelling using our own implementation are quantified. It is highly advisable to model the interfaces strictly, since the implicit modelling might lead to relevant errors in object space.</p>

Abstract. Artificial reefs provide an efficient way to improve marine life abundance in the oceans, including growth on the structure itself. Photogrammetric methods provide suitable tools to measure marine growth. This paper focusses on cubic reefs placed in Western Australia. The capturing platform featured a photogrammetric multi-sensor system for unmanned underwater vehicles attached to a low-cost vehicle BlueROV2. The multi-sensor system and its photogrammetric data captured was calibrated, adjusted and analyzed employing a structure-from-motion processing pipeline. Novel automated image masking techniques were developed and applied to the data to significantly reduce noise in the derived dense point clouds. Results show improvements of signal to noise ratio of more than 50 %, while maintaining a complete representation of the observed artificial reef.