KLT Tracking MATLAB Implementation (Simple Version)

This document introduces a KLT (Kanade-Lucas-Tomasi) tracking code implementation for MATLAB, designed as a simple tracking version.

The KLT algorithm is widely used for feature point tracking in video sequences. This algorithm tracks feature points across image frames and analyzes their movement patterns to estimate object motion. Due to its high tracking accuracy and fast processing speed, KLT has become one of the most commonly used algorithms in computer vision applications. The implementation typically involves feature point detection using corner detection methods, optical flow computation between consecutive frames, and iterative refinement of point positions.

This MATLAB code is specifically written for video processing applications and includes complete implementation of the KLT algorithm along with video frame reading capabilities and tracking result visualization. The code structure comprises several key functions: video frame extraction using VideoReader, feature point initialization with minimum eigenvalue calculation, pyramidal Lucas-Kanade optical flow computation for robust tracking, and trajectory visualization through plotting functions. Users can easily execute KLT tracking in MATLAB by running the main script, which handles the entire pipeline from video input to motion trajectory display.