The goal of human tracking is to detect people in a scene and assign them a unique identifier that the tracker will follow across multiple frames. Our tracker, FORT, implements deep learning solutions such as, YOLOv7 for detection, ResNeXt- 50 for feature extraction and re-identification and an adapted Kalman filter for tracking. The goal is to present a real time tracking solution for the complex environment of top-view, fisheye images. The proposed solution is then compared with the BoTSORT and StrongSORT trackers on a custom fisheye Multiple Object Tracking (MOT) Challenge dataset