This book addresses Assistive Augmentation, highlighting the design and development of assistive technologies, user interfaces, and interactions that seamlessly integrate with a user's mind, body, and behavior, providing an enhanced perception. Our senses are the dominant channel we use to perceive the world around us. Whether they have impairments or not, people often find themselves at the limits of their sensorial capabilities. Some seek assistive or enhancing devices that enable them to carry out specific tasks or even transform them into a "superhuman" with capabilities well beyond the ordinary. The overarching topic of this book revolves around the design and development of technologies and interfaces that provide enhanced physical, sensorial and cognitive capabilities: "Assistive Augmentation". The Assistive Augmentation community convened at an interdisciplinary workshop at the 2014 International Conference on Human Factors in Computing Systems (CHI) in Toronto, Canada. The community is comprised of researchers and practitioners who work at the junction of human-computer interaction, assistive technology and human augmentation. This edited volume, which represents the first tangible outcome of the workshop, presents stimulating discussions on the challenges of Assistive Augmentation as examined through case studies. These studies focus on two main areas: (1) Augmented Sensors and Feedback Modalities, and (2) Design for Assistive Augmentation.

This book addresses Assistive Augmentation, highlighting the design and development of assistive technologies, user interfaces, and interactions that seamlessly integrate with a user's mind, body, and behavior, providing an enhanced perception. Our senses are the dominant channel we use to perceive the world around us. Whether they have impairments or not, people often find themselves at the limits of their sensorial capabilities. Some seek assistive or enhancing devices that enable them to carry out specific tasks or even transform them into a "superhuman" with capabilities well beyond the ordinary. The overarching topic of this book revolves around the design and development of technologies and interfaces that provide enhanced physical, sensorial and cognitive capabilities: "Assistive Augmentation". The Assistive Augmentation community convened at an interdisciplinary workshop at the 2014 International Conference on Human Factors in Computing Systems (CHI) in Toronto, Canada. The community is comprised of researchers and practitioners who work at the junction of human-computer interaction, assistive technology and human augmentation. This edited volume, which represents the first tangible outcome of the workshop, presents stimulating discussions on the challenges of Assistive Augmentation as examined through case studies. These studies focus on two main areas: (1) Augmented Sensors and Feedback Modalities, and (2) Design for Assistive Augmentation.

Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms Key Features Discover best practices for engineering and maintaining OpenCV projects Explore important deep learning tools for image classification Understand basic image matrix formats and filters Book DescriptionOpenCV 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 Millan Escriva Learn OpenCV 4 By Building Projects - Second Edition by David Millan Escriva, Vinicius G. Mendonca, and Prateek Joshi What you will learn Stay up-to-date with algorithmic design approaches for complex computer vision tasks Work with OpenCV's most up-to-date API through various projects Understand 3D scene reconstruction and Structure from Motion (SfM) Study camera calibration and overlay augmented reality (AR) using the ArUco module Create CMake scripts to compile your C++ application Explore segmentation and feature extraction techniques Remove backgrounds from static scenes to identify moving objects for surveillance Work with new OpenCV functions to detect and recognize text with Tesseract Who this book is forIf 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.

Work on practical computer vision projects covering advanced object detector techniques and modern deep learning and machine learning algorithms Key Features Learn about the new features that help unlock the full potential of OpenCV 4 Build face detection applications with a cascade classifier using face landmarks Create an optical character recognition (OCR) model using deep learning and convolutional neural networks Book DescriptionMastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You'll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You'll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You'll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4. What you will learn Build real-world computer vision problems with working OpenCV code samples Uncover best practices in engineering and maintaining OpenCV projects Explore algorithmic design approaches for complex computer vision tasks Work with OpenCV's most updated API (v4.0.0) through projects Understand 3D scene reconstruction and Structure from Motion (SfM) Study camera calibration and overlay AR using the ArUco Module Who this book is forThis book is for those who have a basic knowledge of OpenCV and are competent C++ programmers. You need to have an understanding of some of the more theoretical/mathematical concepts, as we move quite quickly throughout the book.