| View Larger Image | An Introduction to 3D Computer Vision Techniques and Algorithms | Hardcoverby Boguslaw Cyganek (Author), J. Paul Siebert (Author)
| List Price: | $140.00 | | Price: | $112.00 | | You Save: | $28.00 (20%) | | | Available: | Usually ships in 24 hours |
| | Binding: | Hardcover | | Publisher: | Wiley | | Page Count: | 504 Pages | | Publication Date: | March 03, 2009 | | Sales Rank: | 575,679th |
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EDITORIAL REVIEWS |
Product Description
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. |
CUSTOMER REVIEWS (Average Customer Rating: 4.5 based on 2 reviews)
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Quite complete and easy to understand by Alberto Irurueta (Barcelona, Spain)  5 Stars
May 15, 2009
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.
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state of the art for 2008 by W Boudville (Terra, Sol 3)  4 Stars
March 14, 2009
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.
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