Dynamic Object Tracking in Video Sequences using MATLAB

In this article, we explore the implementation of dynamic object tracking using MATLAB. Dynamic object tracking refers to the technology of following moving targets within video sequences. Over the past decades, this technique has gained widespread adoption, particularly in security and surveillance industries. With MATLAB, we can efficiently implement dynamic object tracking with excellent results through computer vision approaches. Key implementation aspects include motion detection algorithms (like background subtraction using vision.ForegroundDetector), object feature extraction (using functions such as extractHOGFeatures or detectSURFFeatures), and tracking methods (such as Kalman filters via vision.KalmanFilter or correlation filters). The workflow typically involves preprocessing video frames with VideoReader, segmenting moving objects, and maintaining trajectory consistency using prediction-correction mechanisms. This technology finds applications in numerous fields including video surveillance systems, motion analysis in sports science, and robotic vision for autonomous navigation. Ultimately, this article demonstrates MATLAB-based dynamic object tracking implementation along with its practical applications across various domains.