IOU Region Merging

Intersection-over-Union (IoU) region merging is a technique used to improve the accuracy and efficiency of object detection and tracking, particularly in challenging scenarios like sports analysis, autonomous driving, and fish behavior studies. Current research focuses on enhancing IoU calculations by incorporating contextual information (e.g., ego-centric perspective for safety, spatio-temporal relationships for tracking) and integrating it with various model architectures, including Mask R-CNN and deep learning-based trackers. These advancements lead to improved performance metrics (e.g., HOTA, MOTA, mAP) across diverse applications, ultimately contributing to more robust and reliable automated systems for various fields.