A multi-object video tracking method based on spatial constraints

Aiming at technical advantages of quickly discover and real-time tracking focused on targets with UAV video, we propose a multi-object tracking method based on spatial constraints. Utilizing the pre-training model of YOLOv7, we do a little work of model modification with UAVDT dataset and a small self-made dataset, then train a special object detection model for identifying and positioning vehicles in the battlefield environment; according to features of battlefield environment, we adopt classification and grading association method to determine the correlation between detection box and object, and propose a data association method based on spatial constraints and object re-identification, compared to current popular algorithms, which effectively improved the ID_SW and reduce the number of object ID switching.