An Introduction to 3D Computer Vision Techniques and Algorithms [Hardcover]

Boguslaw Cyganek (Author), J. Paul Siebert (Author)

Book Description

ISBN-10: 047001704X | ISBN-13: 978-0470017043 | Publication Date: March 4, 2009 | Edition: 1

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, case studies and exercises. 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 Algorithms and Techniques 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.

Editorial Reviews

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.

About the Author

Boguslaw Cyganek, AGH – University of Science and Technology, Department of Computer Science, Signal Processing Laboratory, Krakow, Poland

Boguslaw Cyganek has been teaching at the AGH – University of Science and Technology since 1993 and is now a Lecturer and Researcher in the Department of Electronics and Computer Science. His research interests include the development of image processing systems, robot vision and neural networks. During this time, he has gained several years of practical experience working as a Software Development Manager and a Software Engineer both in the USA and Poland. He has also written Three Dimensional Image Processing (Academic Publisher House, 2002) and 18 academic papers on image processing and algorithms.

Paul Siebert, Department of Computing Science, University of Glasgow, 3D-MATIC Research Laboratory, Scotland

Dr Jan Paul Siebert is currently Director of the 3D-MATIC Research Laboratory in the Department of Computing Science at Glasgow University. His research interests are in computer vision, image processing, and 3D imaging by stereo photogrammetry and its applications in 3D whole human body imaging. He is Scottish Chair of the BMVC and prior to his current position he was Chief Executive of the of the Turing Institute, Glasgow, which developed the ‘C3D’ imaging technology. He has written over 50 journal, technical and conference papers on 3D image processing, modelling virtual images and photogrammetry.

Product Details

• Hardcover: 504 pages
• Publisher: Wiley; 1 edition (March 4, 2009)
• Language: English
• ISBN-10: 047001704X
• ISBN-13: 978-0470017043
• Product Dimensions: 9.8 x 6.8 x 1.3 inches
• Shipping Weight: 2.2 pounds (View shipping rates and policies)
• Average Customer Review: 4.5 out of 5 stars  See all reviews (2 customer reviews)
• Amazon Best Sellers Rank: #992,141 in Books (See Top 100 in Books)

More About the Author

Discover books, learn about writers, read author blogs, and more.

Customer Reviews

Most Helpful Customer Reviews

5 of 5 people found the following review helpful:

5.0 out of 5 stars Quite complete and easy to understand, May 15, 2009

By 

Alberto Irurueta (Barcelona, Spain) - See all my reviews
(REAL NAME)   

This review is from: An Introduction to 3D Computer Vision Techniques and Algorithms (Hardcover)

Although Hartley's book offers a deeper perspective on stereo 3D reconstruction, it is also aimed at an audience with a higher knowledge on this area, both mathematically and conceptually.
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.

2 of 5 people found the following review helpful:

4.0 out of 5 stars state of the art for 2008, March 14, 2009

By 

W Boudville (Terra, Sol 3) - See all my reviews
(VINE VOICE)    (TOP 1000 REVIEWER)    (HALL OF FAME REVIEWER)    (REAL NAME)   

This review is from: An Introduction to 3D Computer Vision Techniques and Algorithms (Hardcover)

For professional researchers in computer vision, this book is useful as a summation of the state of the art for 2008. It is comparable to Davies' Machine Vision : Theory, Algorithms, Practicalities (Signal Processing and its Applications) from 2004.

The text starts with a general outline of the problem, giving basic ideas and deploying the maths needed in many of the algorithms. Tensor analysis is widely used and you need to be familiar with it.

As befitting the title, little space is devoted to 2D image recognition. The far more difficult problem is to identify "strong" characteristics of a desired object embedded in a 3D space. Methods like Haar transforms are invoked. But overall, the human eye, backed up by the brain's wetware, is still a more robust detector. The state of the art has further to progress.