This is a Cookbook with plenty of practical recipes enriched with explained code and relevant screenshots to ease your learning curve. If you are a beginner or a professional in NIUI and want to write serious applications or games, then this book is for you. Even OpenNI 1 and OpenNI 1.x programmers who want to move to new versions of OpenNI can use this book as a starting point. This book uses C++ as the primary language but there are some examples in C# and Java too, so you need to have about a basic working knowledge of C or C++ for most cases.

Over 35 hands-on recipes to create impressive, stunning visuals for a wide range of real-time, interactive applications using OpenGL About This Book Get acquainted with a set of fundamental OpenGL primitives and concepts that enable users to create stunning visuals of arbitrarily complex 2D and 3D datasets for many common applications Explore interactive, real-time visualization of large 2D and 3D datasets or models, including the use of more advanced techniques such as stereoscopic 3D rendering. Create stunning visuals on the latest platforms including mobile phones and state-of-the-art wearable computing devices Who This Book Is For This book is aimed at anyone interested in creating impressive data visualization tools using modern graphics hardware. Whether you are a developer, engineer, or scientist, if you are interested in exploring the power of OpenGL for data visualization, this book is for you. While familiarity with C/C++ is recommended, no previous experience with OpenGL is assumed. What You Will Learn Install, compile, and integrate the OpenGL pipeline into your own project Create interactive applications using GLFW to handle user inputs and the Android Sensor framework to detect gestures and motions on mobile devices Use OpenGL primitives to plot 2-D datasets such as time series dynamically Render complex 3D volumetric datasets with techniques such as data slicers and multiple viewpoint projection Render images, videos, and point cloud data from 3D range-sensing cameras using the OpenGL Shading Language (GLSL) Develop video see-through augmented reality applications on mobile devices with OpenGL ES 3.0 and OpenCV Visualize 3D models with meshes and surfaces using stereoscopic 3D technology In Detail OpenGL is a great multi-platform, cross-language, and hardware-accelerated graphics interface for visualizing large 2D and 3D datasets. Data visualization has become increasingly challenging using conventional approaches as datasets become larger and larger, especially with the Big Data evolution. From a mobile device to a sophisticated high-performance computing cluster, OpenGL libraries provide developers with an easy-to-use interface to create stunning visuals in 3D in real time for a wide range of interactive applications. This book provides a series of easy-to-follow, hands-on tutorials to create appealing OpenGL-based visualization tools with minimal development time. We will first illustrate how to quickly set up the development environment in Windows, Mac OS X, and Linux. Next, we will demonstrate how to visualize data for a wide range of applications using OpenGL, starting from simple 2D datasets to increasingly complex 3D datasets with more advanced techniques. Each chapter addresses different visualization problems encountered in real life and introduces the relevant OpenGL features and libraries in a modular fashion. By the end of this book, you will be equipped with the essential skills to develop a wide range of impressive OpenGL-based applications for your unique data visualization needs, on platforms ranging from conventional computers to the latest mobile/wearable devices. Style and approach This is an easy-to-follow, comprehensive Cookbook showing readers how to create an application with real-time, interactive data visualization in stereoscopic 3D. Each topic is explained in a step-by-step format. A range of hot topics is included, including data visualization on mobile and wearable platforms.

Explore OpenCV 4 to create visually appealing cross-platform computer vision applications Key FeaturesUnderstand basic OpenCV 4 concepts and algorithmsGrasp advanced OpenCV techniques such as 3D reconstruction, machine learning, and artificial neural networksWork with Tesseract OCR, an open-source library to recognize text in imagesBook Description 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. Whether you’re completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects – Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. You’ll begin with the installation of OpenCV and the basics of image processing. Then, you’ll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module. By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch. What you will learnInstall OpenCV 4 on your operating systemCreate CMake scripts to compile your C++ applicationUnderstand basic image matrix formats and filtersExplore segmentation and feature extraction techniquesRemove backgrounds from static scenes to identify moving objects for surveillanceEmploy various techniques to track objects in a live videoWork with new OpenCV functions for text detection and recognition with TesseractGet acquainted with important deep learning tools for image classificationWho this book is for 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, Learn OpenCV 4 by Building Projects for you. Prior knowledge of C++ will help you understand the concepts covered in this book.

Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3 About This Book Get to grips with the basics of Computer Vision and image processing This is a step-by-step guide to developing several real-world Computer Vision projects using OpenCV 3 This book takes a special focus on working with Tesseract OCR, a free, open-source library to recognize text in images Who This Book Is For 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 Open CV, this is the book for you. Knowledge of C++ is required. What You Will Learn Install OpenCV 3 on your operating system Create the required CMake scripts to compile the C++ application and manage its dependencies Get to grips with the Computer Vision workflows and understand the basic image matrix format and filters Understand the segmentation and feature extraction techniques Remove backgrounds from a static scene to identify moving objects for video surveillance Track different objects in a live video using various techniques Use the new OpenCV functions for text detection and recognition with Tesseract In Detail Open CV is a cross-platform, free-for-use library that is primarily used for real-time Computer Vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. Whether you are completely new to the concept of Computer Vision or have a basic understanding of it, this book will be your guide to understanding the basic OpenCV concepts and algorithms through amazing real-world examples and projects. Starting from the installation of OpenCV on your system and understanding the basics of image processing, we swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly used Computer Vision techniques to build your own Open CV projects from scratch. By the end of this book, you will be familiar with the basics of Open CV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition. Style and approach This book is a practical guide with lots of tips, and is closely focused on developing Computer vision applications with OpenCV. Beginning with the fundamentals, the complexity increases with each chapter. Sample applications are developed throughout the book that you can execute and use in your own projects.

Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms Key FeaturesDiscover best practices for engineering and maintaining OpenCV projectsExplore important deep learning tools for image classificationUnderstand basic image matrix formats and filtersBook Description 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: Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán EscriváLearn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek JoshiWhat you will learnStay up-to-date with algorithmic design approaches for complex computer vision tasksWork with OpenCV's most up-to-date API through various projectsUnderstand 3D scene reconstruction and Structure from Motion (SfM)Study camera calibration and overlay augmented reality (AR) using the ArUco moduleCreate CMake scripts to compile your C++ applicationExplore segmentation and feature extraction techniquesRemove backgrounds from static scenes to identify moving objects for surveillanceWork with new OpenCV functions to detect and recognize text with TesseractWho this book is for 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. Prior knowledge of C++ and familiarity with mathematical concepts will help you better understand the concepts in this Learning Path.

Leverage the power of ROS to build exciting collaborative robots. Key Features Delve into an open source, meta-operating system for your robot Get acquainted with tools and libraries for building and running code on multiple platforms Use Gazebo to model your robot and create a virtual environment Book Description This book will leverage the power of ROS with an introduction to its core and advanced concepts through exciting recipes. You will get acquainted with the use of different synchronous and asynchronous communication methods, including messages, services, and actions. You will learn how to use the various debugging and visualization tools used in development and how to interface sensors and actuators with the ROS framework. Firstly, you will get to grips with ROS simulation frameworks, such as Gazebo and RotorS for modeling and simulating any physical robot and virtual environment. You will also cover mobile robotics, micro-aerial vehicles, and robotic arms, which are the leading branches of robotic applications. Robot Operating System Cookbook will also guide you in the development of an autonomous navigation framework for both mobile robots and micro-aerial vehicles. Finally, you will explore ROS-Industrial, an open source project that extends the advanced capabilities of ROS software to manufacturing industries. What you will learn Explore advanced concepts, such as ROS pluginlib, nodelets, and actionlib Work with ROS visualization, profiling, and debugging tools Gain experience in robot modeling and simulation using Gazebo Understand the ROS Navigation Stack for mobile robots Configure a MoveIt! package for a manipulator robot Develop an autonomous navigation framework for MAV using ORB SLAM and MoveIt Integrate sensors, actuators, and robots into the ROS ecosystem Get acquainted with the ROS-Industrial package with hardware support, capabilities, and applications Who this book is for If you’re a researcher or engineer with an interest in the problems, solutions, and future research issues that you may encounter in the development of robotic applications, this book is for you. Basic knowledge of C++ and Python programming with the GNU/Linux environment is strongly recommended to assist with understanding the key concepts covered in the book.