Building a video retrieval system that is robust and reliable, especially for the marine environment, is a challenging task due to several factors such as dealing with massive amounts of dense and repetitive data, occlusion, blurriness, low lighting conditions, and abstract queries. To address these challenges, we present MarineVRS, a novel and flexible video retrieval system designed explicitly for the marine domain. MarineVRS integrates state-of-the-art methods for visual and linguistic object representation to enable efficient and accurate search and analysis of vast volumes of underwater video data. In addition, unlike the conventional video retrieval system, which only permits users to index a collection of images or videos and search using a free-form natural language sentence, our retrieval system includes an additional Explainability module that outputs the segmentation masks of the objects that the input query referred to. This feature allows users to identify and isolate specific objects in the video footage, leading to more detailed analysis and understanding of their behavior and movements. Finally, with its adaptability, explainability, accuracy, and scalability, MarineVRS is a powerful tool for marine researchers and scientists to efficiently and accurately process vast amounts of data and gain deeper insights into the behavior and movements of marine species.

翻译：构建一个鲁棒且可靠的视频检索系统（特别是在海洋环境中）是一项极具挑战性的任务，主要因为海量密集重复数据、遮挡模糊、弱光照条件及抽象查询等多重因素。针对这些挑战，我们提出了MarineVRS——一个专为海洋领域设计的新型灵活视频检索系统。该系统通过整合视觉与语言对象表征的最先进方法，实现对海量水下视频数据的高效精准检索与分析。与传统仅支持图像/视频集索引和自然语言自由查询的视频检索系统不同，我们的系统额外集成了可解释性模块，能输出查询所指向对象的语义分割掩码。这一特性使用户能够识别并分离视频片段中的特定对象，从而更深入地分析其行为模式与运动轨迹。凭借其自适应性、可解释性、精确性与可扩展性，MarineVRS将成为海洋研究科学家高效精准处理海量数据、洞悉海洋生物行为规律的重要工具。