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 hyperlapse 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
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This book is ideal for you if you aspire to build computer vision systems that are smarter, faster, 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.
Joseph Howse lives in Canada. During the cold winters, he grows a beard and his four cats grow thick coats of fur. He combs the cats every day. Sometimes, the cats pull his beard. Joseph has been writing for Packt Publishing since 2012. His books include OpenCV for Secret Agents, OpenCV 3 Blueprints, Android Application Programming with OpenCV 3, Learning OpenCV 3 Computer Vision with Python, and Python Game Programming by Example. When he is not writing books or grooming cats, Joseph provides consulting, training, and software development services through his company, Nummist Media (http://nummist.com). Steven Puttemans is a PhD research candidate at the KU Leuven, Department of Industrial Engineering Sciences. At this university, he is working for the EAVISE research group, which focuses on combining computer vision and artificial intelligence. He obtained a master of science degree in Electronics-ICT and further expanded his interest in computer vision by obtaining a master of science in artificial intelligence. As an enthusiastic researcher, his goal is to combine state-of-the-art computer vision algorithms with real-life industrial problems to provide robust and complete object detection solutions for the industry. His previous projects include TOBCAT, an open source object detection framework for industrial object detection problems, and a variety of smaller computer vision-based industrial projects. During these projects, Steven worked closely with the industry. Steven is also an active participant in the OpenCV community. He is a moderator of the OpenCV Q&A forum, and has submitted or reviewed many bug fixes and improvements for OpenCV 3. He also focuses on putting as much of his research as possible back into the framework to further support the open source spirit. More info about Steven's research, projects, and interests can be found at https://stevenputtemans.github.io. Quan Hua is a software engineer at Autonomous, a start-up company in robotics, where he focuses on developing computer vision and machine learning applications for personal robots. He earned a bachelor of science degree from the University of Science, Vietnam, specializing in computer vision, and published a research paper in CISIM 2014. As the owner of Quan404.com, he also blogs about various computer vision techniques to share his experience with the community.
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