Learn something new in an Instant! A short, fast, focused guide delivering immediate results
Build and run your OpenCV code on iOS
Become familiar with iOS fundamentals and make your application interact with the GUI, camera, and gallery
Build your library of computer vision effects, including photo and video filters

In Detail

Computer vision on mobile devices is becoming more and more popular. Personal gadgets are now powerful enough to process high-resolution images, stitch panoramas, and detect and track objects. OpenCV, with its decent performance and wide range of functionality, can be an extremely useful tool in the hands of iOS developers.

Instant OpenCV for iOS is a practical guide that walks you through every important step for building a computer vision application for the iOS platform. It will help you to port your OpenCV code, profile and optimize it, and wrap it into a GUI application. Each recipe is accompanied by a sample project or an example that helps you focus on a particular aspect of the technology.

Instant OpenCV for iOS starts by creating a simple iOS application and linking OpenCV before moving on to processing images and videos in real-time. It covers the major ways to retrieve images, process them, and view or export results. Special attention is also given to performance issues, as they greatly affect the user experience.Several computer vision projects will be considered throughout the book. These include a couple of photo filters that help you to print a postcard or add a retro effect to your images. Another one is a demonstration of the facial feature detection algorithm. In several time-critical cases, the processing speed is measured and optimized using ARM NEON and the Accelerate framework.

OpenCV for iOS gives you all the information you need to build a high-performance computer vision application for iOS devices.

What you will learn from this book

Build a simple iOS application with GUI and controls
Link OpenCV to your project and call it from the Objective C code
Load and save images to the gallery
Interact with the camera and control its advanced settings
Implement several photo effects
Process video streams from the camera in real-time and save it in H.264 format
Detect faces and facial features and minimize the detection speed
Use the Accelerate framework to optimize the performance

Approach

Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. This book uses a very practical approach, with each recipe and their associated sample projects or examples focusing on a particular aspect of the technology.

Who this book is written for

This book is intended for OpenCV developers who are interested in porting their applications to the iOS platform. Basic experience with OpenCV, computer vision, Objective C, and other iOS tools is encouraged.

About the Author

Kirill Kornyakov has been a member of the core OpenCV development team for the last four years. He works at Itseez (Nizhny Novgorod, Russia), where he leads the development of the OpenCV library for the Android operating system, with a focus on performance optimization for the NVIDIA Tegra platform. He also works on the implementation of real-time computer vision algorithms, mainly Computational Photography applications. Kirill has B.Sc. and M.Sc. degrees from Nizhny Novgorod State University, Russia. Alexander Shishkov has been working in the field of computer vision for the last five years. He works at Itseez (Nizhny Novgorod, Russia), where he has developed technologies such as video-based people counting systems, object detection, and image retrieval systems. He also created continuous integration system and websites (http://opencv.org) for OpenCV. Alexander has B.Sc. and M.Sc. degrees from Nizhny Novgorod State University, Russia.

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