Citizen Science and Gamification to Foster Data-Driven Sea Floor Exploration

Marine scientists increasingly rely on underwater imagery to study and monitor the seafloor. However, creating reliable datasets for image matching remains a major challenge because underwater environments are highly dynamic, visually complex, and rarely provide accurate ground truth. Factors such as water turbidity, changing illumination, suspended particles, and repetitive textures make establishing correspondences between images difficult, limiting the development and evaluation of computer vision algorithms.

Our project aims to tackle this challenge by building a citizen science platform that leverages gamification to involve the public in scientific data annotation. Through an intuitive and engaging web interface, users are invited to identify matching features between pairs of underwater images. By turning annotation into an interactive experience, we enable large-scale collection of human-generated image correspondences while making marine science accessible to a broader audience.

The resulting annotations will be aggregated into a high-quality dataset of underwater image matches that can serve as valuable ground truth for research in computer vision, robotics, and autonomous underwater exploration. By combining human intelligence with modern data-driven methods, our platform helps bridge the gap between citizen participation and scientific discovery, ultimately contributing to more robust algorithms for mapping, monitoring, and exploring the ocean floor.