MATLAB Tracking Source Code: Centroid and Bounding Box Methods for Moving Object Detection

In this article, we present a MATLAB-based tracking solution for detecting and following moving objects within a scene. The implementation utilizes centroid calculation algorithms to determine the object's center point and rectangular bounding box methods to define the object's spatial extent. These complementary approaches enable more accurate position tracking and trajectory estimation. The MATLAB code processes video frames sequentially, employing background subtraction techniques to isolate moving objects. Key functions include regionprops() for centroid calculation and bounding box generation, along with motion vector analysis for trajectory prediction. The implementation handles object detection through image segmentation and morphological operations to improve tracking reliability. We also demonstrate how MATLAB's visualization tools can be used to analyze tracking data, displaying object paths, velocity profiles, and movement patterns through plot() and imshow() functions. Data analysis includes trajectory smoothing using interpolation methods and statistical evaluation of movement characteristics. Towards the conclusion, we provide additional resources and references for further exploration of computer vision and tracking methodologies. This article aims to enhance understanding of MATLAB tracking implementations while offering practical guidance for real-world applications in motion analysis and object monitoring scenarios.