Building Computer Vision Projects with OpenCV 4 and C++: Implement complex computer vision algorithms and explore deep learning and face detection
bDelve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms/b h4Key Features/h4 ul liDiscover best practices for engineering and maintaining OpenCV projects /li liExplore important deep learning too...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing Limited
2019
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| Ausgabe: | 1 |
| Schlagworte: | |
| Zusammenfassung: | bDelve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms/b h4Key Features/h4 ul liDiscover best practices for engineering and maintaining OpenCV projects /li liExplore important deep learning tools for image classification /li liUnderstand basic image matrix formats and filters/li /ul h4Book Description/h4 OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: ul liMastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millan Escriva/li liLearn OpenCV 4 By Building Projects - Second Edition by David Millan Escriva, Vinicius G. Mendonca, and Prateek Joshi/li /ul h4What you will learn/h4 ul liStay up-to-date with algorithmic design approaches for complex computer vision tasks /li liWork with OpenCV's most up-to-date API through various projects /li liUnderstand 3D scene reconstruction and Structure from Motion (SfM) /li liStudy camera calibration and overlay augmented reality (AR) using the ArUco module /li liCreate CMake scripts to compile your C++ application /li liExplore segmentation and feature extraction techniques /li liRemove backgrounds from static scenes to identify moving objects for surveillance /li liWork with new OpenCV functions to detect and recognize text with Tesseract/li/ul h4Who this book is for/h4 If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. |
| Beschreibung: | 1 Online-Ressource (538 Seiten) |
| ISBN: | 9781838641269 |
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| 520 | |a bDelve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms/b h4Key Features/h4 ul liDiscover best practices for engineering and maintaining OpenCV projects /li liExplore important deep learning tools for image classification /li liUnderstand basic image matrix formats and filters/li /ul h4Book Description/h4 OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. | ||
| 520 | |a In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: ul liMastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millan Escriva/li liLearn OpenCV 4 By Building Projects - Second Edition by David Millan Escriva, Vinicius G. | ||
| 520 | |a Mendonca, and Prateek Joshi/li /ul h4What you will learn/h4 ul liStay up-to-date with algorithmic design approaches for complex computer vision tasks /li liWork with OpenCV's most up-to-date API through various projects /li liUnderstand 3D scene reconstruction and Structure from Motion (SfM) /li liStudy camera calibration and overlay augmented reality (AR) using the ArUco module /li liCreate CMake scripts to compile your C++ application /li liExplore segmentation and feature extraction techniques /li liRemove backgrounds from static scenes to identify moving objects for surveillance /li liWork with new OpenCV functions to detect and recognize text with Tesseract/li/ul h4Who this book is for/h4 If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. | ||
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| 700 | 1 | |a Shilkrot, Roy |e Sonstige |4 oth | |
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| id | DE-604.BV047069552 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:13:33Z |
| indexdate | 2024-07-10T09:01:43Z |
| institution | BVB |
| isbn | 9781838641269 |
| language | English |
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| spelling | Millan Escriva, David Verfasser aut Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection Millan Escriva, David 1 Birmingham Packt Publishing Limited 2019 1 Online-Ressource (538 Seiten) txt rdacontent c rdamedia cr rdacarrier bDelve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms/b h4Key Features/h4 ul liDiscover best practices for engineering and maintaining OpenCV projects /li liExplore important deep learning tools for image classification /li liUnderstand basic image matrix formats and filters/li /ul h4Book Description/h4 OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: ul liMastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millan Escriva/li liLearn OpenCV 4 By Building Projects - Second Edition by David Millan Escriva, Vinicius G. Mendonca, and Prateek Joshi/li /ul h4What you will learn/h4 ul liStay up-to-date with algorithmic design approaches for complex computer vision tasks /li liWork with OpenCV's most up-to-date API through various projects /li liUnderstand 3D scene reconstruction and Structure from Motion (SfM) /li liStudy camera calibration and overlay augmented reality (AR) using the ArUco module /li liCreate CMake scripts to compile your C++ application /li liExplore segmentation and feature extraction techniques /li liRemove backgrounds from static scenes to identify moving objects for surveillance /li liWork with new OpenCV functions to detect and recognize text with Tesseract/li/ul h4Who this book is for/h4 If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. COMPUTERS / Intelligence (AI) & Semantics COMPUTERS / Programming Languages / C++ Joshi, Prateek Sonstige oth G. Mendonca, Vinicius Sonstige oth Shilkrot, Roy Sonstige oth |
| spellingShingle | Millan Escriva, David Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection COMPUTERS / Intelligence (AI) & Semantics COMPUTERS / Programming Languages / C++ |
| title | Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection |
| title_auth | Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection |
| title_exact_search | Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection |
| title_exact_search_txtP | Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection |
| title_full | Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection Millan Escriva, David |
| title_fullStr | Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection Millan Escriva, David |
| title_full_unstemmed | Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection Millan Escriva, David |
| title_short | Building Computer Vision Projects with OpenCV 4 and C++ |
| title_sort | building computer vision projects with opencv 4 and c implement complex computer vision algorithms and explore deep learning and face detection |
| title_sub | Implement complex computer vision algorithms and explore deep learning and face detection |
| topic | COMPUTERS / Intelligence (AI) & Semantics COMPUTERS / Programming Languages / C++ |
| topic_facet | COMPUTERS / Intelligence (AI) & Semantics COMPUTERS / Programming Languages / C++ |
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