Human Detection and Tracking using Machine Learning Algorithm

Abstract

The use of OpenCV and its capabilities for person tracking and detection is suggested by this project. The technique works well for following people in a variety of situations, such as busy places, people who are obscured, and people who are moving. The robustness and precision of the estimated model are illustrated through the use of visuals to visualize tracking data. The suggested approach surpasses existing sophisticated algorithms in terms of Intersection over Union (IoU) and mean Average Precision (mAP), achieving excellent accuracy. Potential applications for the proposed method include robots, human-computer interaction, and surveillance. The limits of the suggested approach are also covered, along with suggestions for further research and development.