Tracking of Mobile Phones for Piracy Detection

Abstract: The film industry has faced challenges with unauthorized reproduction and distribution of movies. To combat this issue, we propose an innovative system that employs IP cameras, Python, and a regular computer to detect instances of piracy in real-time and inform the relevant parties. Our solution uses a specialized object detection model trained with a set of images of the item to be detected, particularly mobile phones, which are associated with piracy. We utilized the YOLOv5 repository to construct the model, which can provide precise bounding box data to indicate the object's exact location in the frame. Additionally, the system includes a mail service that notifies the theater owner or other authorized individuals of piracy occurrences and provides them with an image of the incident. This allows them to take prompt action. The system operates in real-time and can monitor live feeds from multiple cameras at once to detect any piracy instances immediately.

Keywords: MoviePiracy, Yolov5, IP camera.