OpenCV Programming for Android on Linux Tutorial -5 NDK Installation and Configuration

In this tutorial I show how to download, install, and configure the Native Development Kit (NDK) on Eclipse running on a Linux desktop. I show how to run and upload an OpenCV native C/C++ application to a mobile device running the Android operating system. For source code download and installation guide visit my website http://www.stemapks.com/ Android is an open-source software stack for a wide range of mobile devices and a corresponding open-source project led by Google. Here you can find the information and source code you need to learn more about the Android platform. From there you can create custom variants of the Android software stack, port devices and accessories to the Android platform, and ensure your devices are compatible with the Android compatibility definition. Android's purpose is to establish an open platform for developers to build innovative apps. The Android Compatibility program defines the technical details of the Android platform and provides tools used by OEMs to ensure that developers' apps run on a variety of devices. The Android SDK provides built-in tools that developers use to clearly state the device features their apps require. And Google Play shows apps only to those devices that can properly run them. OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people in their user community and an estimated number of downloads exceeding 7 million. The library is used extensively in companies, research groups and by governmental bodies. email: [email protected] twitter: https://twitter.com/Cesco345 git: https://github.com/cesco345