9781849517836: Mastering OpenCV with Practical Computer Vision Projects

In Detail

OpenCV is a computer vision library that is extensively used in companies, research groups and governmental bodies for real-time capture, video file import, image manipulation, object detection and much more. Its comprehensive set of computer vision and machine learning algorithms makes it the obvious choice for professionals to develop visual applications.

With this book in hand, you would not need to plow through several pages of theory as this book will take you through the creation of many exciting projects that showcase the huge range of possibilities that open up when OpenCV is exploited to its full potential.

Approach

Using a project-based approach you will learn fun and challenging aspects of OpenCV computer vision application development. With each project you will be able to show off a creation that utilizes OpenCV’s features to its maximum potential.

Who this book is for

This book is for researchers, programmers, and software developers who know the basics of OpenCV and are interested in building computer vision applications themselves.

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Über den Autor:

Shervin Emami (born in Iran) taught himself electronics and hobby robotics during his early teens in Australia. While building his first robot at the age of 15, he learned how RAM and CPUs work. He was so amazed by the concept that he soon designed and built a whole Z80 motherboard to control his robot, and wrote all the software purely in binary machine code using two push buttons for 0s and 1s. After learning that computers can be programmed in much easier ways such as assembly language and even high-level compilers, Shervin became hooked to computer programming and has been programming desktops, robots, and smartphones nearly every day since then. During his late teens he created Draw3D (http://draw3d.shervinemami.info/), a 3D modeler with 30,000 lines of optimized C and assembly code that rendered 3D graphics faster than all the commercial alternatives of the time; but he lost interest in graphics programming when 3D hardware acceleration became available. In University, Shervin took a subject on computer vision and became highly interested in it; so for his first thesis in 2003 he created a real-time face detection program based on Eigenfaces, using OpenCV (beta 3) for camera input. For his master's thesis in 2005 he created a visual navigation system for several mobile robots using OpenCV (v0.96). From 2008, he worked as a freelance Computer Vision Developer in Abu Dhabi and Philippines, using OpenCV for a large number of short-term commercial projects that included: Detecting faces using Haar or Eigenfaces, Recognizing faces using Neural Networks, EHMM, or Eigenfaces, Detecting the 3D position and orientation of a face from a single photo using AAM and POSIT, Rotating a face in 3D using only a single photo, Face preprocessing and artificial lighting using any 3D direction from a single photo, Gender recognition, Facial expression recognition, Skin detection, Iris detection, Pupil detection, Eye-gaze tracking, Visual-saliency tracking, Histogram matching, Body-size detection, Shirt and bikini detection, Money recognition, Video stabilization, Face recognition on iPhone, Food recognition on iPhone, Marker-based augmented reality on iPhone (the second-fastest iPhone augmented reality app at the time). OpenCV was putting food on the table for Shervin's family, so he began giving back to OpenCV through regular advice on the forums and by posting free OpenCV tutorials on his website (http://www.shervinemami.info/openCV.html). In 2011, he contacted the owners of other free OpenCV websites to write this book. He also began working on computer vision optimization for mobile devices at NVIDIA, working closely with the official OpenCV developers to produce an optimized version of OpenCV for Android. In 2012, he also joined the Khronos OpenVL committee for standardizing the hardware acceleration of computer vision for mobile devices, on which OpenCV will be based in the future. Khvedchenia Ievgen is a computer vision expert from Ukraine. He started his career with research and development of a camera-based driver assistance system for Harman International. He then began working as a Computer Vision Consultant for ESG. Nowadays, he is a self-employed developer focusing on the development of augmented reality applications. Ievgen is the author of the Computer Vision Talks blog (http://computer-vision-talks.com), where he publishes research articles and tutorials pertaining to computer vision and augmented reality. Naureen Mahmood is a recent graduate from the Visualization department at Texas A&M University. She has experience working in various programming environments, animation software, and microcontroller electronics. Her work involves creating interactive applications using sensor-based electronics and software engineering. She has also worked on creating physics-based simulations and their use in special effects for animation. Here is her blog - http://howdweknows.blogspot.com/

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