Kalman Filter-Based Video Sequence Frame Tracking
A MATLAB implementation of Kalman filter-based tracking for video sequence frames, featuring state-space modeling and recursive prediction-correction algorithms for object motion trajectory analysis.
Target Tracking Algorithms: CamShift and MeanShift
Exploration of CamShift and MeanShift algorithms for object tracking, including implementation approaches and code-level insights for computer vision applications.
Tracking and Extraction of Fingerprint Ridgelines
This process involves tracing and extracting fingerprint ridgelines from pre-thinned fingerprint images using advanced ridge tracking algorithms.
Implementation of 3D Target Tracking and Monitoring
This program achieves 3D target tracking and monitoring using the Extended Kalman Filter (EKF) algorithm, which handles nonlinear systems through linear approximation and recursive state estimation.
Reading Video Frames and Motion Object Detection & Tracking Using MATLAB
A comprehensive guide to extracting image frames from video files using MATLAB, with implementation of motion object detection and tracking algorithms including background subtraction, frame differencing, optical flow methods, Kalman filters, and particle filters.
Multi-Target Tracking Using PDA Probabilistic Data Association Algorithm
Implementation of PDA probabilistic data association algorithm for tracking multiple targets in a 2D plane using MATLAB, including sensor data processing and trajectory estimation
Tracking and Localization of Indoor Sound Sources
Implementation approaches for tracking and positioning sound sources in reverberant indoor environments, including algorithmic considerations.
Optical Flow Algorithm with MATLAB Implementation
A MATLAB source program implementing optical flow algorithm, widely applicable in image processing, foreground detection, and object tracking - recommended for computer vision applications
MATLAB Implementation of Kalman Filter Algorithm for Motion Trajectory Estimation
Implementation of the Kalman filter algorithm for tracking and estimating object motion trajectories using MATLAB routines and simulation techniques. The solution includes state prediction, measurement updates, and covariance matrix handling for optimal trajectory estimation.
Unscented Particle Filter Routine
Unscented Particle Filter routine with a simple tracking application. Implementation in a clutter-free environment demonstrates core algorithm performance.