Explore MATLAB source code curated for "计算机视觉" with clean implementations, documentation, and examples.
This implementation constructs a Gaussian Mixture Model (GMM) designed for computer vision applications including video object detection, video surveillance, motion detection, moving object detection, and video object tracking. The code features parameter optimization and expectation-maximization algorithm implementation for robust multi-modal data modeling.
MIT AI Laboratory's object recognition source code, implemented in MATLAB, is highly suitable for computer vision research, featuring practical algorithm implementations and core computer vision techniques.
MATLAB source code for Incremental Learning for Robust Visual Tracking algorithm, published in International Journal of Computer Vision (IJCV), Volume 77, Issues 1-3, pages 125-141, 2008. Features real-time object tracking implementation with online learning capabilities.
MATLAB Implementation for Rapid Fundamental Matrix Estimation in Multi-View Geometry
MATLAB implementation of Local Binary Pattern (LBP) feature extraction algorithm for computer vision applications, including image processing techniques and feature vector generation methods.
Disparity maps serve as the foundation for numerous computer vision applications, functioning as limited 3D models that enable depth perception through stereo matching algorithms like block-matching or semi-global matching.
The Gabor filter is renowned for approximating the receptive field properties of the visual cortex in human vision systems. Recent advancements in computer vision applications demonstrate the technique's proven success and promising potential. This directory provides implementation code for Gabor filtering with detailed explanations of filter bank construction strategies in the accompanying paper.
Using MATLAB for simulated cube reconstruction serves as a fundamental experimental application in computer vision for 3D reconstruction, involving key steps like image preprocessing, point cloud generation, and surface modeling.
Neural Network Approach to License Plate Recognition with Technical Implementation Details
This algorithm employs the Hough transform for straight-line detection of lane markings, with implementation details including edge detection preprocessing and parameter space optimization.