BoT-SORT is a tracking-by-detection system that associates object detections across video frames while maintaining unique identifiers. It combines YOLOX and YOLOv7 neural network detectors for object detection with appearance-based re-identification features and Kalman filtering for motion prediction. The system achieves state-of-the-art results on MOTChallenge benchmarks by integrating camera motion compensation and robust data association algorithms.