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Multiple View Geometry in Computer Vision
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This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied.
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What Stands Out
Rincian Produk
- Second edition of the book Multiple View Geometry in Computer Vision.
- Contains comprehensive and updated information on computer vision techniques.
- Covers essential topics such as camera calibration and 3D reconstruction.
- Includes detailed explanations and algorithms for multiple view geometry.
- Written by leading experts in the field of computer vision and geometry.
- A valuable resource for researchers, practitioners, and students in computer vision.
| Publisher | Cambridge University Press |
| Publication date | March 25, 2004 |
| Edition | 2nd |
| Language | English |
| Print length | 670 pages |
| ISBN-10 | 0521540518 |
| ISBN-13 | 978-0521540513 |
| Item Weight | 3.23 pounds (1.47 kg) |
| Dimensions | 7 x 0.25 x 9.5 inches (17.8 x 0.6 x 24.1 cm) |
Who Should Buy?
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Computer Vision Students
Ideal for students studying computer vision, providing foundational concepts and advanced topics in multiple view geometry.
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Research Professionals
Beneficial for researchers requiring in-depth knowledge of 3D reconstruction and camera calibration techniques.
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Industry Practitioners
Useful for practitioners in technology sectors implementing computer vision in applications such as robotics and augmented reality.
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Casual Learners
Not suitable for casual learners seeking an introductory guide, as it covers complex mathematical concepts and theories.
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Multiple View Geometry in Computer Vision
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Computer Vision & Pattern Recognition Editorial Review
Multiple View Geometry in Computer Vision is a comprehensive resource published by Cambridge University Press on March 25, 2004. This 670-page book is aimed at explaining complex concepts in a digestible format, with clear explanations of 2D and 3D geometry, single and two-view geometry, and trifocal geometry, making it beneficial for researchers. The authored text is recognized for its rigorous approach to projective geometry and computational algorithms, providing readers with well-structured content carefully illustrated with practical explanations. While it is immensely helpful for advanced researchers, beginners may find it challenging without a solid foundation in linear algebra and computer vision.
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Pro
- Clear explanations and motivation for complex topics
- Comprehensive resource for computer vision researchers
- Well-structured content with practical illustrations
- Rigorously detailed discussion of algorithms
- Useful Matlab code available on the website
Kontra
- Might be complex for beginners without prior knowledge
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Fitur & Manfaat
- Covers relevant geometric principles in computer vision
- Explains how to represent objects algebraically for computation
- Describes recent major developments in scene reconstruction
- Provides comprehensive background material
- Explains how to apply the methods and implement the algorithms
- Second edition released, first edition published in 2000
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