[b]Название[/b]: MATLAB & Simulink Computer Vision Toolbox User's Guide (R2021a)
Автор: MathWorks
Издательство: The MathWorks, Inc.
Год: 2021
Страниц: 1340
Язык: английский
Формат: pdf (true)
Размер: 57.5 MB

Проектируйте и тестируйте компьютерное зрение, 3D Vision и системы обработки видео. Computer Vision Toolbox предоставляет алгоритмы, функции и приложения для проектирования и тестирования компьютерного зрения, 3D Vision и систем обработки видео. Вы можете выполнить обнаружение и отслеживание объектов, а также обнаружение функций, экстракцию и сопоставление.

Design and test computer vision, 3D vision, and video processing systems.

Computer Vision Toolbox provides algorithms, functions, and apps for designing and testing computer vision, 3D vision, and video processing systems. You can perform object detection and tracking, as well as feature detection, extraction, and matching. For 3D vision, the toolbox supports single, stereo, and fisheye camera calibration; stereo vision; 3D reconstruction; and lidar and 3D point cloud processing. Computer vision apps automate ground truth labeling and camera calibration workflows.

You can train custom object detectors using deep learning and machine learning algorithms such as YOLO v2, Faster R-CNN, and ACF. For semantic segmentation you can use deep learning algorithms such as SegNet, U-Net, and DeepLab. Pretrained models let you detect faces, pedestrians, and other common objects.

You can accelerate your algorithms by running them on multicore processors and GPUs. Most toolbox algorithms support C/C++ code generation for integrating with existing code, desktop prototyping, and embedded vision system deployment.

Contents:

Camera Calibration Examples
Code Generation and Third-Party Examples
Deep Learning, Semantic Segmentation, and Detection Examples
Feature Detection and Extraction Examples
Lidar and Point Cloud Processing Examples
Computer Vision with Simulink Examples
Video and Image Ground Truth Labeling
Tracking and Motion Estimation Examples
Featured Examples
Structure from Motion and Visual SLAM
Point Cloud Processing
Using the Installer for Computer Vision System Toolbox Product
Input, Output, and Conversions
Display and Graphics
Registration and Stereo Vision
Object Detection
Motion Estimation and Tracking
Filters, Transforms, and Enhancements
Statistics and Morphological Operations
Fixed-Point Design
Code Generation and Shared Library
Vision Blocks Examples








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