SquidJam: A Video Annotation Ecosystem

2023 IEEE Underwater Technology (UT)(2023)

引用 0|浏览15
暂无评分
摘要
Analyses of marine ecosystems requires recording and observing large volumes of images and videos collected from various underwater platforms. In our work, we extensively use multi-camera systems mounted on Remotely Operated Vehicles (ROV) for obtaining videos of marine organisms. Along with these, ocean physico-chemical parameters such as temperature, salinity, oxygen concentration, vehicle position, etc. are also recorded. Analysis of videos and images is labor intensive and automated approaches are necessary to overcome this bottleneck. We use the annotation software Squidle+ for on-site and post-cruise annotations. Squidle+ allows combining images as well as corresponding metadata for annotations made by users and saves them it in a database. We developed an integrated system, built upon the Squidle+ annotation platform, that includes extensions to annotate and post-process multiple video data streams from ROVs with their associated metadata. Details of this SquidJam ecosystem are described in this paper. This ecosystem has allowed us to integrate and reduce time required for many tasks performed on the annotations to make scientific analyses.
更多
查看译文
关键词
Annotations,Marine ecosystems,Scientific analyses
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要