Computer Vision–Based Object Tracking System Assisted by a PID Controller

Abstract

The study aimed to identify the applications of artificial intelligence that can be benefited from in the development of the video and surveillance camera system. There are challenges and problems related to the following aspects (monitoring process - identifying shapes - tracking them. And by employing some artificial intelligence applications in the monitoring process, such as object recognition and tracking systems, where the tasks of object recognition and tracking in video surveillance and monitoring systems are a key element, and color detection to track the target with real-time video sequences. The system described in this paper is on a camera attached to a Raspberry Pi board, containing an image processing algorithm (Haarcascade) that first detects the object and then tracks it. Color detection is generally a key stage in most image processing applications, if the application is based on color information. To monitor the object in the video, a built-in panel is adopted to monitor the activity of the object of interest based on the Raspberry PI panel. A real-time execution software method is implemented to track the object of interest. Animated and recognized using the Python programming language with OpenCV libraries. The two algorithms are tested and compared to  prove the robustness of the object detection algorithm.