构建首个面向海事环境的多模态目标检测与跟踪数据集，支持小型障碍物识别。
PoLaRIS Dataset: A Maritime Object Detection and Tracking Dataset in Pohang Canal
- 采集图像与点标注的多模态数据，覆盖波浪干扰下的动态海况
- 包含最小10×10像素的障碍物标注，满足高精度导航需求
- 适用于海洋机器人安全避障研究，尤其适合复杂海面场景算法验证
由于船只、浮标等移动物体在波浪影响下可能成为障碍物，海事环境常存在安全隐患。为保障海洋机器人安全航行，精准检测与跟踪潜在危险目标至关重要。针对现有数据集在动态海况下覆盖不足的问题，我们提出PoLaRIS数据集，包含图像与点标注的多模态数据，提供障碍物检测与跟踪的详细真值信息。数据集涵盖最小10×10像素的目标，对海事安全具有重要意义。通过采用多种主流方法（包括当前最优技术）进行评估，验证了该数据集作为可靠基准的有效性，有望推动复杂海事环境下检测与跟踪性能的提升。据我们所知，这是首个专为海事环境设计的多模态标注数据集，相关资源已公开：https://sites.google.com/view/polaris-dataset。
原文摘要 · Abstract (English)
Maritime environments often present hazardous situations due to factors such as moving ships or buoys, which become obstacles under the influence of waves. In such challenging conditions, the ability to detect and track potentially hazardous objects is critical for the safe navigation of marine robots. To address the scarcity of comprehensive datasets capturing these dynamic scenarios, we introduce a new multi-modal dataset that includes image and point-wise annotations of maritime hazards. Our dataset provides detailed ground truth for obstacle detection and tracking, including objects as small as 10$\times$10 pixels, which are crucial for maritime safety. To validate the dataset's effectiveness as a reliable benchmark, we conducted evaluations using various methodologies, including \ac{SOTA} techniques for object detection and tracking. These evaluations are expected to contribute to performance improvements, particularly in the complex maritime environment. To the best of our knowledge, this is the first dataset offering multi-modal annotations specifically tailored to maritime environments. Our dataset is available at https://sites.google.com/view/polaris-dataset.
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