Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB
Bangjun Lei, Guangzhu Xu, Ming Feng, Yaobin Zou, Ferdinand van der Heijden, Dick de Ridder, David M. J. Tax
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商品描述
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.
商品描述(中文翻譯)
一本關於智能電腦視覺理論、設計、實作與技術的實用入門書籍
過去十年見證了影像處理和智能電腦視覺技術的巨大成長。機器學習方法的進步,特別是在adaboost變種和粒子過濾方法方面,使得智能電腦視覺中的機器學習比以往任何時候都更準確和可靠。對於這個蓬勃發展領域的最新技術專業知識的需求從未如此迫切,而本書正是滿足這一需求的作品。這本經過全面更新和廣泛修訂的《第二版》流行指南,為設計師、數據分析師、研究人員和高級研究生提供了對智能電腦視覺的基本而又完全實用的介紹。作者將帶領讀者了解電腦視覺的基礎知識,回顧過去和現在,並探討智能電腦視覺的更微妙的複雜性,重點放在智能測量系統上。通過許多及時的現實世界範例,他們解釋並生動展示了影像和視頻處理技術及其在電腦視覺系統中機器學習的最新發展,包括:
- PRTools5軟體,特別是最新的PRTools5表示和泛化軟體工具箱
- 電腦視覺的機器學習應用,詳細討論當代狀態估計技術與舊有的粒子過濾方法內容的比較
- 最新的分類和監督學習技術,重點在於神經網絡、遺傳狀態估計及其他粒子過濾和人工智慧狀態估計方法
- 全新涵蓋的Adaboost及其在PRTools5中的實作
這本《第二版》對於專業人士來說是一個有價值的工作資源,對於高級學生來說則是極好的入門書籍,書中包含了大量的示例,從基本技術到高級智能電腦視覺系統的實作。此外,還可以在伴隨網站上找到更多示例和教程,以及問題和解決方案論壇。