Book Image

Instant OpenCV for iOS

4 (1)
Book Image

Instant OpenCV for iOS

4 (1)

Overview of this book

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.
Table of Contents (7 chapters)

About the Authors

Kirill Kornyakov has been a member of core OpenCV development team for the last 4 years. He works at Itseez (Nizhny Novgorod, Russia), where he leads the development of an OpenCV library for the Android operating system, with a focus on performance optimization for the NVIDIA Tegra platform. He also works on 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.