Motion Detection and Tracking Source Code Developed by International Researchers
MATLAB-based motion detection and tracking algorithms with comprehensive code implementation and technical documentation
SIFT Algorithm
The SIFT algorithm effectively identifies corresponding feature points across different images, demonstrating strong utility in tracking and graphical recognition applications, typically implemented through multi-scale feature detection and descriptor generation.
MATLAB Source Code for Face Recognition and Tracking
MATLAB source code for face recognition and tracking, featuring advanced algorithm implementation with robust detection and real-time tracking capabilities.
Road Edge and Lane Detection and Tracking Package
This MATLAB package provides executable road edge and lane detection and tracking algorithms with excellent experimental performance, featuring robust image processing techniques and computer vision implementations.
Simulate 2D GPS Object Tracking and Apply Kalman Filter for Trajectory Smoothing
Simulate GPS-based 2D object tracking and enhance trajectory accuracy using Kalman filter smoothing algorithms with noise reduction implementation.
Unscented Kalman Filter
Unscented Kalman Filter - Primarily applied for tracking in nonlinear systems, implementing sigma point transformation for improved state estimation accuracy.
Adaptive Mobile Target Tracking for Smart Antenna Systems
Implementation of mobile target tracking for adaptive smart antennas using Kalman filter algorithm with provided source code
Excellent Resource on Tracking and Acquisition in Spread Spectrum Communication Systems
This resource provides valuable materials on tracking and acquisition in spread spectrum communications, offering significant assistance for receiver design and implementation through practical code-level insights.
Moving Object Detection and Tracking Algorithms with MATLAB Implementation
MATLAB code repository for moving object detection and tracking, including experimental data and comprehensive code explanations. Features algorithm implementations for background subtraction, optical flow, and object tracking methods. Ideal for research in pedestrian detection, intelligent transportation systems, and video surveillance applications.
3D Radar Tracking Particle Filter Implementation
A highly optimized MATLAB implementation of a three-dimensional radar tracking particle filter, featuring robust performance in high-noise environments with exceptional precision.