{"title":"Take good care of your fish: fish re-identification with synchronized multi-view camera system","authors":"Suzhen Fan, Chengyang Song, Haiyang Feng, Zhibin Yu","doi":"10.3389/fmars.2024.1429459","DOIUrl":null,"url":null,"abstract":"IntroductionFish re-identification (re-ID) is of great significance for fish monitoring and can contribute to aquaculture and fish breeding. Synchronizing information from different cameras is beneficial for optimizing re-ID performance.MethodsWe constructed the first underwater fish re-identification benchmark dataset (FS48) under three camera conditions. FS48 encompasses 48 different fish identities, 10,300 frames, and 39,088 bounding boxes, covering various lighting conditions and background environments. Additionally, we developed the first robust and accurate fish re-identification baseline, FSNet, which fuses information from three camera positions by extracting features from synchronized video frames of each position and combining the synchronized information.ResultsThe experimental results show that FS48 is universal and of high quality. FSNet has an effective network design and demonstrates good performance, achieving better re-identification performance by combining information from three positions, helping improve overall re-test accuracy, and evaluating the effectiveness of re-identification among detectors.DiscussionOur dataset will be released upon acceptance of this paper, which is expected to further promote the development of underwater fish re-identification.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"3 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Marine Science","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3389/fmars.2024.1429459","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MARINE & FRESHWATER BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
IntroductionFish re-identification (re-ID) is of great significance for fish monitoring and can contribute to aquaculture and fish breeding. Synchronizing information from different cameras is beneficial for optimizing re-ID performance.MethodsWe constructed the first underwater fish re-identification benchmark dataset (FS48) under three camera conditions. FS48 encompasses 48 different fish identities, 10,300 frames, and 39,088 bounding boxes, covering various lighting conditions and background environments. Additionally, we developed the first robust and accurate fish re-identification baseline, FSNet, which fuses information from three camera positions by extracting features from synchronized video frames of each position and combining the synchronized information.ResultsThe experimental results show that FS48 is universal and of high quality. FSNet has an effective network design and demonstrates good performance, achieving better re-identification performance by combining information from three positions, helping improve overall re-test accuracy, and evaluating the effectiveness of re-identification among detectors.DiscussionOur dataset will be released upon acceptance of this paper, which is expected to further promote the development of underwater fish re-identification.
期刊介绍:
Frontiers in Marine Science publishes rigorously peer-reviewed research that advances our understanding of all aspects of the environment, biology, ecosystem functioning and human interactions with the oceans. Field Chief Editor Carlos M. Duarte at King Abdullah University of Science and Technology Thuwal is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, policy makers and the public worldwide.
With the human population predicted to reach 9 billion people by 2050, it is clear that traditional land resources will not suffice to meet the demand for food or energy, required to support high-quality livelihoods. As a result, the oceans are emerging as a source of untapped assets, with new innovative industries, such as aquaculture, marine biotechnology, marine energy and deep-sea mining growing rapidly under a new era characterized by rapid growth of a blue, ocean-based economy. The sustainability of the blue economy is closely dependent on our knowledge about how to mitigate the impacts of the multiple pressures on the ocean ecosystem associated with the increased scale and diversification of industry operations in the ocean and global human pressures on the environment. Therefore, Frontiers in Marine Science particularly welcomes the communication of research outcomes addressing ocean-based solutions for the emerging challenges, including improved forecasting and observational capacities, understanding biodiversity and ecosystem problems, locally and globally, effective management strategies to maintain ocean health, and an improved capacity to sustainably derive resources from the oceans.