Computer Vision, Fifth Edition: Principles, Algorithms, Applications, Learning

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Computer Vision, Fifth Edition: Principles, Algorithms, Applications, Learning (英语) 精装 – 2017年11月29日
E. R. Davies (作者)

Computer Vision: Principles, Algorithms, Applications, Learning (previously entitled Computer and Machine Vision) clearly and systematically presents the basic methodology of computer vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This fully revised fifth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date text suitable for undergraduate and graduate students, researchers and R&D engineers working in this vibrant subject.
See an interview with the author explaining his approach to teaching and learning computer vision - http://scitechconnect.elsevier.com/computer-vision/

Three new chapters on Machine Learning emphasise the way the subject has been developing; Two chapters cover Basic Classification Concepts and Probabilistic Models; and the The third covers the principles of Deep Learning Networks and shows their impact on computer vision, reflected in a new chapter Face Detection and Recognition.
A new chapter on Object Segmentation and Shape Models reflects the methodology of machine learning and gives practical demonstrations of its application.
In-depth discussions have been included on geometric transformations, the EM algorithm, boosting, semantic segmentation, face frontalisation, RNNs and other key topics.
Examples and applications―including the location of biscuits, foreign bodies, faces, eyes, road lanes, surveillance, vehicles and pedestrians―give the ‘ins and outs’ of developing real-world vision systems, showing the realities of practical implementation.
Necessary mathematics and essential theory are made approachable by careful explanations and well-illustrated examples.
The ‘recent developments’ sections included in each chapter aim to bring students and practitioners up to date with this fast-moving subject.
Tailored programming examples―code, methods, illustrations, tasks, hints and solutions (mainly involving MATLAB and C++)

基本信息

出版社: Academic Press; 5 (2017年11月29日)
精装: 900页
语种： 英语
ISBN: 012809284X
条形码: 9780128092842
商品尺寸: 19.7 x 5.1 x 24.1 cm
商品重量: 1.88 Kg
ASIN: 012809284X

1. Vision, the Challenge

2. Images and Imaging Operations

3. Image Filtering and Morphology

4. The Role of Thresholding

5. Edge Detection

6. Corner, Interest Point and Invariant Feature Detection

7. Texture Analysis

8. Binary Shape Analysis

9. Boundary Pattern Analysis

10. Line, Circle and Ellipse Detection

11. The Generalised Hough Transform

12. Object Segmentation and Shape Models

13. Basic Classification Concepts

14. Machine Learning: Probabilistic Methods

15. Deep Learning Networks

16. The Three-Dimensional World

17. Tackling the Perspective n-point Problem

18. Invariants and perspective

19. Image transformations and camera calibration

20. Motion

21. Face Detection and Recognition: the Impact of Deep Learning

22. Surveillance

23. In-Vehicle Vision Systems

24. Epilogue―Perspectives in Vision

Appendix A:Robust statistics

Appendix B: The Sampling Theorem

Appendix C: The representation of colour

Appendix D: Sampling from distributions

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