Simple Object Tracking for Human Motion

In this experiment, we implemented object tracking for human motion using MATLAB with the Kalman Filter approach. Kalman Filter is a mathematical method widely used in control systems and signal processing, which employs statistical techniques to estimate and predict system states. For our implementation, we utilized MATLAB's Computer Vision Toolbox functions such as vision.KalmanFilter to create a tracking system that predicts human motion trajectories. The algorithm works by continuously updating state estimates through prediction and correction steps - first predicting the object's next position, then correcting based on actual measurements. This approach helps us better understand the characteristics and patterns of human movement. Through this experiment, we demonstrate how to implement basic object tracking in MATLAB, including key aspects like state initialization, motion model configuration, and measurement validation. The implementation covers fundamental Kalman Filter concepts and their practical applications in motion tracking scenarios.