PC

Android Application Programming with OpenCV

by Joseph Howse

333 pages - 2013 - 5.8 MB New!

Take a smartphone from your pocket, and within a few seconds, you can snap a photo, manipulate it, and share it with the world. You have just achieved mass production of image data. With a computer vision library such as OpenCV, you can analyze and transform copious amounts of image data in real time on a mobile device. The upshot to this is that you, as developers, can provide mobile users with many new kinds of images, constantly highlighting certain visual features that are of artistic or practical interest. Android is a convenient platform for such experiments because it uses a high-level language (Java), it provides standardized interfaces for sharing image data between applications, and it is mostly open source, so everyone can study its implementation.

PC

OpenCV Computer Vision with Python

by Joseph Howse

333 pages - 2015 - 1.39 MB New!

Learn to capture videos, manipulate images, and track objects with Python using the OpenCV Library Overview Set up OpenCV, its Python bindings, and optional Kinect drivers on Windows, Mac or Ubuntu Create an application that tracks and manipulates faces Identify face regions using normal color images and depth images In Detail Computer Vision can reach consumers in various contexts via webcams, camera phones and gaming sensors like Kinect. OpenCV’s Python bindings can help developers meet these consumer demands for applications that capture images, change their appearance and extract information from them, in a high-level language and in a standardized data format that is interoperable with scientific libraries such as NumPy and SciPy. “OpenCV Computer Vision with Python” is a practical, hands-on guide that covers the fundamental tasks of computer vision—capturing, filtering and analyzing images—with step-by-step instructions for writing both an application and reusable library classes. “OpenCV Computer Vision with Python” shows you how to use the Python bindings for OpenCV. By following clear and concise examples you will develop a computer vision application that tracks faces in live video and applies special effects to them. If you have always wanted to learn which version of these bindings to use, how to integrate with cross-platform Kinect drivers and and how to efficiently process image data with NumPy and SciPy then this book is for you. What you will learn from this book Install OpenCV and related software such as Python, NumPy, SciPy, OpenNI, and SensorKinect—all on Windows, Mac or Ubuntu Capture, display, and save photos and real-time videos Handle window events and input events using OpenCV’s HighGui module or Pygame Understand OpenCV’s image format and how to perform efficient operations on OpenCV images with NumPy and SciPy Apply “curves” and other color transformations to simulate the look of old photos, movies or video games Apply an effect only to edges in an image Copy and resize segments of an image Apply an effect only to certain depths in an image by using data from a depth sensor such as Kinect Track faces, eyes, noses and mouths by using prebuilt datasets Track arbitrary objects by creating original datasets Approach A practical, project-based tutorial for Python developers and hobbyists who want to get started with computer vision with OpenCV and Python. Who this book is written for OpenCV Computer Vision with Python is written for Python developers who are new to computer vision and want a practical guide to teach them the essentials. Some understanding of image data (for example, pixels and color channels) would be beneficial. At a minimum you will need access to at least one webcam. Certain exercises require additional hardware like a second webcam, a Microsoft Kinect or an OpenNI-compliant depth sensor such as the Asus Xtion PRO.

PC

Android Application Programming with OpenCV 3

by Joseph Howse

333 pages - 2015 - 5.53 MB New!

Android Application Programming with OpenCV 3 is a practical, hands-on guide to computer vision and mobile app development. It shows how to capture, manipulate, and analyze images while building an application that combines photography and augmented reality. To help the reader become a well-rounded developer, the book covers OpenCV (a computer vision library), Android SDK (a mobile app framework), OpenGL ES (a 3D graphics framework), and even JNI (a Java/C++ interoperability layer).

PC

OpenCV 3 Blueprints

by Joseph Howse

333 pages - 2015 - 13.53 MB New!

Expand your knowledge of computer vision by building amazing projects with OpenCV 3 About This Book Build computer vision projects to capture high-quality image data, detect and track objects, process the actions of humans or animals, and much more Discover practical and interesting innovations in computer vision while building atop a mature open-source library, OpenCV 3 Familiarize yourself with multiple approaches and theories wherever critical decisions need to be made Who This Book Is For This book is ideal for you if you aspire to build computer vision systems that are smarter, faster, more complex, and more practical than the competition. This is an advanced book intended for those who already have some experience in setting up an OpenCV development environment and building applications with OpenCV. You should be comfortable with computer vision concepts, object-oriented programming, graphics programming, IDEs, and the command line. What You Will Learn Select and configure camera systems to see invisible light, fast motion, and distant objects Build a “camera trap” as used by nature photographers, and process photos to create beautiful effects Develop a facial expression recognition system with various feature extraction techniques and machine learning methods Build a panorama Android application using the OpenCV stitching module in C++ with NDK support Optimize your object detection model, make it rotation invariant, and apply scene-specific constraints to make it faster and more robust Create a person identification and registration system based on biometric properties of that person, such as their fingerprint, iris, and face Fuse data from videos and gyroscopes to stabilize videos shot from your mobile phone and create hyper lapse style videos In Detail Computer vision is becoming accessible to a large audience of software developers who can leverage mature libraries such as OpenCV. However, as they move

PC

OpenCV for Secret Agents

by Joseph Howse

333 pages - 2014 - 6.29 MB New!

OpenCV is a grand collection of image processing functions and computer vision algorithms. It is open source, it supports many programming languages and platforms, and it is fast enough for many real-time applications. What a lot of gadgets we can build with such a handy library!

PC

iOS Application Development with OpenCV 3

by Joseph Howse

333 pages - 2016 - 5.8 MB New!

iOS Application Development with OpenCV 3 enables you to turn your smartphone camera into an advanced tool for photography and computer vision. Using the highly optimized OpenCV library, you will process high-resolution images in real time. You will locate and classify objects, and create models of their geometry. As you develop photo and augmented reality apps, you will gain a general understanding of iOS frameworks and developer tools, plus a deeper understanding of the camera and image APIs.