{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T21:24:34Z","timestamp":1773869074108,"version":"3.50.1"},"reference-count":70,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,3,21]],"date-time":"2023-03-21T00:00:00Z","timestamp":1679356800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005908","name":"Parliament of the Federal Republic of Germany via the Federal Office for Agriculture and Food (BLE)","doi-asserted-by":"publisher","award":["2819111618"],"award-info":[{"award-number":["2819111618"]}],"id":[{"id":"10.13039\/501100005908","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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%.<\/jats:p>","DOI":"10.3390\/s23063311","type":"journal-article","created":{"date-parts":[[2023,3,21]],"date-time":"2023-03-21T06:56:48Z","timestamp":1679381808000},"page":"3311","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["A Deep-Learning Based Pipeline for Estimating the Abundance and Size of Aquatic Organisms in an Unconstrained Underwater Environment from Continuously Captured Stereo Video"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6196-9558","authenticated-orcid":false,"given":"Gordon","family":"B\u00f6er","sequence":"first","affiliation":[{"name":"Institute of Applied Computer Science, Kiel University of Applied Sciences, 24149 Kiel, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joachim Paul","family":"Gr\u00f6ger","sequence":"additional","affiliation":[{"name":"GEOMAR Helmholtz Centre for Ocean Research Kiel, 24148 Kiel, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sabah","family":"Badri-H\u00f6her","sequence":"additional","affiliation":[{"name":"Institute of Communications Technology and Microelectronics, University of Applied Sciences, 24149 Kiel, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1130-6107","authenticated-orcid":false,"given":"Boris","family":"Cisewski","sequence":"additional","affiliation":[{"name":"Th\u00fcnen Institute of Sea Fisheries, 27572 Bremerhaven, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Helge","family":"Renkewitz","sequence":"additional","affiliation":[{"name":"Fraunhofer IOSB, IOSB-AST Ilmenau, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation, 98693 Ilmenau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Felix","family":"Mittermayer","sequence":"additional","affiliation":[{"name":"Research Unit Marine Evolutionary Ecology, GEOMAR Helmholtz Centre for Ocean Research Kiel, 24148 Kiel, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tobias","family":"Strickmann","sequence":"additional","affiliation":[{"name":"Research Unit Marine Evolutionary Ecology, GEOMAR Helmholtz Centre for Ocean Research Kiel, 24148 Kiel, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hauke","family":"Schramm","sequence":"additional","affiliation":[{"name":"Institute of Applied Computer Science, Kiel University of Applied Sciences, 24149 Kiel, Germany"},{"name":"Department of Computer Science, Faculty of Engineering, Kiel University, 24118 Kiel, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,21]]},"reference":[{"key":"ref_1","first-page":"82","article-title":"Physical-optical-biological scales relevant to recruitment in large marine ecosystems","volume":"90","author":"Dickey","year":"1990","journal-title":"Am. 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