A practical introduction to intelligent computer vision theory, design, implementation, and technology
The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Advancements in machine learning methods—especially among adaboost varieties and particle filtering methods—have made machine learning in intelligent computer vision more accurate and reliable than ever before. The need for expert coverage of the state of the art in this burgeoning field has never been greater, and this book satisfies that need. Fully updated and extensively revised, this 2nd Edition of the popular guide provides designers, data analysts, researchers and advanced post-graduates with a fundamental yet wholly practical introduction to intelligent computer vision. The authors walk you through the basics of computer vision, past and present, and they explore the more subtle intricacies of intelligent computer vision, with an emphasis on intelligent measurement systems. Using many timely, real-world examples, they explain and vividly demonstrate the latest developments in image and video processing techniques and technologies for machine learning in computer vision systems, including:
- PRTools5 software for MATLAB—especially the latest representation and generalization software toolbox for PRTools5
- Machine learning applications for computer vision, with detailed discussions of contemporary state estimation techniques vs older content of particle filter methods
- The latest techniques for classification and supervised learning, with an emphasis on Neural Network, Genetic State Estimation and other particle filter and AI state estimation methods
- All new coverage of the Adaboost and its implementation in PRTools5.
A valuable working resource for professionals and an excellent introduction for advanced-level students, this 2nd Edition features a wealth of illustrative examples, ranging from basic techniques to advanced intelligent computer vision system implementations. Additional examples and tutorials, as well as a question and solution forum, can be found on a companion website.
Keywords: computer vision; intelligent computer vision; intelligent computer vision technology; intelligent computer system design; computer vision theory and practice; intelligent computer vision system design; intelligent computer vision systems development; PRTools5 software for MATLAB; PRTools5 toolbox; computer vision basics; advanced computer vision theory; advances in intelligent computer vision; machine learning; machine learning in computer vision systems; state-of-the-art computer vision technology; intelligent computer vision examples; intelligent computer vision design examples; intelligent computer systems design and implementation; adaboost; adaboost machine learning in intelligent computer vision; particle filtering; particle filtering methods in computer vision systems; classification and supervised learning in intelligent computer vision; Neural Networks in intelligent computer vision; genetic state estimation in intelligent computer vision; AI state estimation methods for intelligent computer vision; Support Vector Machines in intelligent computer vision; SVM for intelligent computer vision; latent SVM for intelligent computer vision; struct SVM for intelligent computer vision; latent support vector machines in intelligent computer vision; struct support vector machines in intelligent computer vision; pattern recognition in intelligent computer vision systems; video processing with field programmable gate arrays; FPGA and video processing, Pattern Analysis, Pattern Analysis
- Feng, Ming
- Heijden, Ferdinand van der
- Lei, Bangjun
- Ridder, Dick de
- Tax, David M. J.
- Xu, Guangzhu
- Zou, Yaobin
- John Wiley and Sons, Inc.
- Publication year
- Page amount
- 480 pages
- Information Technology, Telecommunications
- eISBN (ePUB)
- Printed ISBN