Computer Vision: A Modern Approach (2版)

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Computer Vision: A Modern Approach 2/E(IE) 2012 <PH>2/E IE 2012 作者：David A. Forsyth, Jean Ponce ISBN：9780273764144 版次：2 年份：2012 出版商：Pearson Education 頁數/規格：791頁/平裝單色 簡介: Description This textbook provides the most complete treatment of modern computer vision methods by two of the leading authorities in the field. This accessible presentation gives both a general view of the entire computer vision enterprise and also offers sufficient detail for students to be able to build useful applications. Students will learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. 目錄: Table of Contents I IMAGE FORMATION 1 Geometric Camera Models 2 Light and Shading 3 Color II EARLY VISION: JUST ONE IMAGE 4 Linear Filters 5 Local Image Features 6 Texture III EARLY VISION: MULTIPLE IMAGES 7 Stereopsis 8 Structure from Motion IV MID-LEVEL VISION 9 Segmentation by Clustering 10 Grouping and Model Fitting 11 Tracking V HIGH-LEVEL VISION 12 Registration 13 Smooth Surfaces and Their Outlines 14 Range Data 15 Learning to Classify 16 Classifying Images 17 Detecting Objects in Images 18 Topics in Object Recognition VI APPLICATIONS AND TOPICS 19 Image-Based Modeling and Rendering 20 Looking at People 21 Image Search and Retrieval VII BACKGROUND MATERIAL 22 Optimization Techniques

Foundations of Computer Vision (Adaptive Computation and Machine Learning series) (1版)

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【簡介】 An accessible, authoritative, and up-to-date computer vision textbook offering a comprehensive introduction to the foundations of the field that incorporates the latest deep learning advances. Machine learning has revolutionized computer vision, but the methods of today have deep roots in the history of the field. Providing a much-needed modern treatment, this accessible and up-to-date textbook comprehensively introduces the foundations of computer vision while incorporating the latest deep learning advances. Taking a holistic approach that goes beyond machine learning, it addresses fundamental issues in the task of vision and the relationship of machine vision to human perception. Foundations of Computer Vision covers topics not standard in other texts, including transformers, diffusion models, statistical image models, issues of fairness and ethics, and the research process. To emphasize intuitive learning, concepts are presented in short, lucid chapters alongside extensive illustrations, questions, and examples. Written by leaders in the field and honed by a decade of classroom experience, this engaging and highly teachable book offers an essential next-generation view of computer vision. Up-to-date treatment integrates classic computer vision and deep learning Accessible approach emphasizes fundamentals and assumes little background knowledge Student-friendly presentation features extensive examples and images Proven in the classroom Instructor resources include slides, solutions, and source code 【目錄】

Healthcare Industry 4.0: Computer Vision-Aided Data Analytics (Computational Intelligence Techniques) 2024

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This book covers computer vision-based applications in digital healthcare industry 4.0, including different computer vision techniques, image classification, image segmentations, and object detection. Various application case studies from domains such as science, engineering, and social networking are introduced, along with their architecture and how they leverage various technologies, such as edge computing and cloud computing. It also covers applications of computer vision in tumor detection, cancer detection, combating COVID-19, and patient monitoring. Features: Provides a state-of-the-art computer vision application in the digital health care industry Reviews advances in computer vision and data science technologies for analyzing information on human function and disability Includes practical implementation of computer vision application using recent tools and software Explores computer vision-enabled medical/clinical data security in the cloud Includes case studies from the leading computer vision integrated vendors like Amazon, Microsoft, IBM, and Google This book is aimed at researchers and graduate students in bioengineering, intelligent systems, and computer science and engineering.