- Hardcover: 504 pages
- Publisher: Wiley; 1 edition (February 9, 2009)
- Language: English
- ISBN-10: 047001704X
- ISBN-13: 978-0470017043
- Product Dimensions: 6.9 x 1.1 x 9.8 inches
- Shipping Weight: 2.2 pounds (View shipping rates and policies)
- Average Customer Review: 3 customer reviews
- Amazon Best Sellers Rank: #1,982,204 in Books (See Top 100 in Books)
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An Introduction to 3D Computer Vision Techniques and Algorithms 1st Edition
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“This text is a valuable reference for practitioners and programmers working in 3D computer vision, image processing and analysis as well as computer visualisation. It would also be of interest to advanced students and researchers in the fields of engineering, computer science, clinical photography, robotics, graphics and mathematics.” (Zentralblatt MATH, 2012)
From the Back Cover
Computer vision encompasses the construction of integrated vision systems and the application of vision to problems of real-world importance. The process of creating 3D models is still rather difficult, requiring mechanical measurement of the camera positions or manual alignment of partial 3D views of a scene. However using algorithms, it is possible to take a collection of stereo-pair images of a scene and then automatically produce a photo-realistic, geometrically accurate digital 3D model.
This book provides a comprehensive introduction to the methods, theories and algorithms of 3D computer vision. Almost every theoretical issue is underpinned with practical implementation or a working algorithm using pseudo-code and complete code written in C++ and MatLab®. There is the additional clarification of an accompanying website with downloadable software. Organised in three parts, Cyganek and Siebert give a brief history of vision research, and subsequently:
- present basic low-level image processing operations for image matching, including a separate chapter on image matching algorithms
- explain scale-space vision, as well as space reconstruction and multiview integration
- demonstrate a variety of practical applications for 3D surface imaging and analysis
- provide concise appendices on topics such as the basics of projective geometry and tensor calculus for image processing, distortion and noise in images plus image warping procedures
An Introduction to 3D Computer Vision Techniques and Algorithms is a valuable reference for practitioners and programmers working in 3D computer vision, image processing and analysis as well as computer visualisation. It would also be of interest to advanced students and researchers in the fields of engineering, computer science, clinical photography, robotics, graphics and mathematics.
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This book on the other hand offers a more simplistic solution but it also offers a good review on disparity and point correspondence estimation, which on Hartley's book is barely covered.
As each of theese books offfers a slightly different point of view on the matter, I suggest having both as good references on the subject.