Create multiplatform computer vision desktop and web applications using the combination of OpenCV and Java
If you are a Java developer, student, researcher, or hobbyist wanting to create computer vision applications in Java then this book is for you. If you are an experienced C/C++ developer who is used to working with OpenCV, you will also find this book very useful for migrating your applications to Java.
All you need is basic knowledge of Java, with no prior understanding of computer vision required, as this book will give you clear explanations and examples of the basics.
OpenCV 3.0 Computer Vision with Java is a practical tutorial guide that explains fundamental tasks from computer vision while focusing on Java development. This book will teach you how to set up OpenCV for Java and handle matrices using the basic operations of image processing such as filtering and image transforms. It will also help you learn how to use Haar cascades for tracking faces and to detect foreground and background regions with the help of a Kinect device. It will even give you insights into server-side OpenCV. Each chapter is presented with several projects that are ready to use. The functionality of these projects is found in many classes that allow developers to understand computer vision principles and rapidly extend or customize the projects for their needs.
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If you are a Java developer, student, researcher, or hobbyist wanting to create computer vision applications in Java then this book is for you. If you are an experienced C/C++ developer who is used to working with OpenCV, you will also find this book very useful for migrating your applications to Java. All you need is basic knowledge of Java, with no prior understanding of computer vision required, as this book will give you clear explanations and examples of the basics.
Daniel Lelis Baggio started his work in computer vision through medical image processing at Instituto do Coracao (InCor), which is a heart institute in Sao Paulo, Brazil, where he worked with intravascular ultrasound (IVUS) image segmentation. After this, he focused on GPGPU and ported that algorithm to work with NVIDIA's CUDA. He also dived into the topic of six degrees of freedom (6DoF), head tracking through a project called EHCI (http://code.google.com/p/ehci/) with the Natural User Interface group. He is also the author of Mastering OpenCV with Practical Computer Vision Projects, Packt Publishing.
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