PoLaRIS Dataset: A Maritime Object Detection and Tracking Dataset in Pohang Canal

TL;DR

The PoLaRIS dataset provides comprehensive multi-modal annotations for maritime object detection and tracking, addressing a critical gap in datasets for safe navigation of marine robots in challenging conditions.

Contribution

This is the first multi-modal maritime dataset with detailed annotations for obstacle detection and tracking, including small objects, to improve maritime safety and research.

Findings

Validated dataset effectiveness with state-of-the-art detection and tracking methods.

Enhanced performance in maritime object detection and tracking tasks.

Facilitated research in complex maritime environments.

Abstract

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.