ALBERT

Description: Optic technologies and methods/procedures are established across all areas and scales in limnic and marine research in Germany and develop further continuously. The working group “Aquatic Optic Technologies” (AOT) constitutes a common platform for knowledge transfer among scientists and users, provides a synergistic environment for the national developer community and will enhance the international visibility of the German activities in this field. This document summarizes the AOT-procedures and -techniques applied by national research institutions. We expect to initiate a trend towards harmonization across institutes. This will facilitate the establishment of open standards, provide better access to documentation, and render technical assistance for systems integration. The document consists of the parts: Platforms and carrier systems outlines the main application areas and the used technologies. Focus parameters specifies the parameters measured by means of optical methods/techniques and indicates to which extent these parameters have a socio-political dimension. Methods presents the individual optical sensors and their underlying physical methods. Similarities denominates the common space of AOT-techniques and applications. National developments lists projects and developer groups in Germany designing optical high-technologies for limnic and marine scientific purposes.

Description: The utilization of stationary underwater cameras is a modern and well-adapted approach to provide a continuous and cost-effective long-term solution to monitor underwater habitats of particular interest. A common goal of such monitoring systems is to gain better insight into the dynamics and condition of populations of various marine organisms, such as migratory or commercially relevant fish taxa. This paper describes a complete processing pipeline to automatically determine the abundance, type and estimate the size of biological taxa from stereoscopic video data captured by the stereo camera of a stationary Underwater Fish Observatory (UFO). A calibration of the recording system was carried out in situ and, afterward, validated using the synchronously recorded sonar data. The video data were recorded continuously for nearly one year in the Kiel Fjord, an inlet of the Baltic Sea in northern Germany. It shows underwater organisms in their natural behavior, as passive low-light cameras were used instead of active lighting to dampen attraction effects and allow for the least invasive recording possible. The recorded raw data are pre-filtered by an adaptive background estimation to extract sequences with activity, which are then processed by a deep detection network, i.e., Yolov5. This provides the location and type of organisms detected in each video frame of both cameras, which are used to calculate stereo correspondences following a basic matching scheme. In a subsequent step, the size and distance of the depicted organisms are approximated using the corner coordinates of the matched bounding boxes. The Yolov5 model employed in this study was trained on a novel dataset comprising 73,144 images and 92,899 bounding box annotations for 10 categories of marine animals. The model achieved a mean detection accuracy of 92.4%, a mean average precision (mAP) of 94.8% and an F1 score of 93%.