Source Code for Video Tracking Using Particle Filter Algorithm

This repository contains MATLAB-based source code implementing particle filtering for video object tracking. The algorithm employs Sequential Importance Resampling (SIR) with pre-initialized parameters including particle count, system noise covariance, and observation models. Key components include: 1) State transition functions handling target dynamics, 2) Observation likelihood calculation using color histograms or feature matching, 3) Systematic resampling to mitigate particle degeneracy. The computationally intensive core operations are accelerated through C++ MEX implementations for real-time performance. To execute: place your AVI-format video in the project directory and update the filename in the video reading command (e.g., replace 'video = myvideo.avi'). The architecture supports modifications for differential frame localization to enhance adaptability across different video sequences. This implementation provides a foundational framework for particle filter applications in computer vision, with opportunities for improvement in occlusion handling and multi-target scenarios. Contributors are welcome to collaborate on algorithm enhancements and optimization techniques.