出版社:高等教育出版社
年代:2009
定价:11.5
本书以全新的角度论述智能化的全自动人脸识别方法,着重阐述如何把诸如模式识别、机器学习、图形图象处理、视频的时空关联、甚至逻辑判断等单一的方法有机地结合在一起,非监督式地从视频中检测和识别人脸,并自动建立和更新相映的数据库。这种识别方法集智能性,自适应性和鲁棒性为一体,将大大提高人脸识别在各行各业的广泛应用。另外,本书综合了世界范围内生物识别,特别是人脸识别研究的最新成果,并提出了广义的人脸检测与识别的归类方法。本书内容新颖、广泛,学术性与实用性强,适用于人脸识别领域的科研人员、教学人员、研究生,对其它生物识别领域的研究,也具有重要的借鉴作用。
1 Introduction
1.1 Face Recognition--Machine Versus Human
1.2 Proposed Approach
1.3 Prospective Applications
1.3.1 Recognition in the Future Intelligent Home
1.3.2 Automotive
1.3.3 Mobile Phone for Children
1.4 Outline
References
2 Fundamentals and Advances in Biometrics and Face Recognition
2.1 Generalized Biometric Recognition
2.2 Cognitive-based Biometric Recognition
2.2.1 Introduction
2.2.2 History of Cognitive Science
2.2.3 Human Brain Structure
2.2.4 Generic Methods in Cognitive Science
2.2.5 Visual Function in Human Brain
2.2.6 General Cognitive-based Object Recognition
2.2.7 Cognitive-based Face Recognition
2.2.8 Inspirations from Cognitive-based Face Recognition
2.3 Machine-based Biometric Recognition
2.3.1 Introduction
2.3.2 Biometric Recognition Tasks
2.3.3 Enrollment--a Special Biometric Procedure
2.3.4 Biometric Methods Overview
2.3.5 Fingerprint Recognition
2.4 Generalized Face Recognition Procedure
2.5 Machine-based Face Detection
2.5.1 Face Detection Categories
2.6 Machine-based Face Tracking
2.7 Machine-based Face Recognition
2.7.1 Overview
2.7.2 Benchmark Studies of Face Recognition
2.7.3 Some General Terms Used in Face Recognition
2.7.4 Recognition Procedures and Methods
2.7.5 Video-based Recognition
2.7.6 Unsupervised and Fully Automatic Approaches
2.8 Summary and Discussions
References
3 Combined Face Detection and Tracking Methods
3.1 Introduction
3.2 Image-based Face Detection
3.2.1 Choice of the Detection Algorithm
3.2.2 Overview of the Detection Algorithm
3.2.3 Face Region Estimation
3.2.4 Face Detection Quality
3.3 Temporal-based Face Detection
3.3.1 Overview
3.3.2 Search Region Estimation
3.3.3 Analysis of Temporal Changes
3.4 Summary
3.5 Further Discussions
References
4 Automatic Face Recognition
4.1 Overview
4.2 Feature Extraction and Encoding
4.3 Matching/Classification
4.3.1 Image-based Classifier
4.3.2 Adaptive Similarity Threshold
4.3.3 Temporal Filtering
4.4 Combined Same Face Decision Algorithms
4.5 Summary
References
5 Unsupervised Face Database Construction
5.1 Introduction
5.2 Backgrounds for Constructing Face Databases
5.2.1 Supervised Learning
5.2.2 Unsupervised Learning
5.2.3 Clustering Analysis
5.3 Database Structure
5.3.1 A Fused Clustering Method
5.3.2 Parameters in the Proposed Structure
5.4 Features of an Optimum Database
References
6 State Machine Based Automatic Procedure
6.1 Introduction
6.2 States Explorations
7 System Implementation
7.1 Introduction
7.2 Typical Hardware Configuration
7.3 Software Implementation
7.3.1 Overview
7.3.2 Implementation Efforts
7.4 Technology Dependent Parameters
7.5 Summary
References
8 Performance Analysis
8.1 Introduction
8.2 Performance of Face Detection
8.3 Performance of Face Recognition
8.4 Performance of Database Construction Algorithms
8.5 Overall Performance of the Whole System
8.5.1 Online Version
8.5.2 Offline Version
8.5.3 Critical Assumptions
8.6 Summary
References
9 Conclusions and Future Directions
9.1 Conclusions
9.2 Future Directions
Index
Machine, based Intelligent Face Recognition discusses the general engineering method of imitating intelligent human brains for video-based face recognition in a fundamental way, which is completely unsupervised,automatic, self-learning,self-updated and robust. It also overviews stateof-the-art researchon cognitive-based biometrics and machine-based biometrics, and especially the advances in face recognition.
This book is intended for scientists, researchers, engineers, and students in the field of computer vision, machine intelligence, and particularly of face recognition.
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出版地 | 北京 | 出版单位 | 高等教育出版社 |
版次 | 1版 | 印次 | 1 |
定价(元) | 11.5 | 语种 | 英文 |
尺寸 | 24 | 装帧 | 精装 |
页数 | 印数 | 320 |
基于机器的智能人脸识别是高等教育出版社于2009.08出版的中图分类号为 TP391.41 的主题关于 面-图像识别-智能系统-研究-英文 的书籍。