Coral Video Segmentation

Coral video segmentation focuses on automatically identifying and outlining coral structures within underwater video footage, aiming to improve the efficiency and accuracy of coral reef monitoring and analysis. Current research employs deep learning models, including transformer architectures and YOLO-based object detection, to achieve this segmentation, often coupled with interactive tools for refinement and morphological analysis. This automated approach offers significant advantages over manual methods, enabling more comprehensive and reliable assessments of coral health, distribution, and growth patterns, ultimately supporting better conservation efforts.