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Addressing the need for a concise and accessible introduction to the complex field of computer vision, this text reinforces its presentation of the essential topics with class-tested exercises. The coverage includes an historical overview of the technology.
- Sales Rank: #1003336 in Books
- Published on: 2014-01-20
- Released on: 2014-01-20
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 1.06" w x 6.13" l, 1.90 pounds
- Binding: Paperback
- 429 pages
From the Author
See also the accompanying website at ccv.wordpress.fos.auckland.ac.nz, lecture notes atcs.auckland.ac.nz/~rklette/709/index.html, and also at
researchgate.net/publication/259196682_Concise_Computer_Vision_-_An_Introduction_into_Theory_and_Algorithms
From the Inside Flap
This is a textbook for a third- or fourth-year undergraduate course on Computer Vision, which is a discipline in science and engineering.
From the Back Cover
Many textbooks on computer vision can be unwieldy and intimidating in their coverage of this extensive discipline. This textbook addresses the need for a concise overview of the fundamentals of this field.
Concise Computer Vision provides an accessible general introduction to the essential topics in computer vision, highlighting the role of important algorithms and mathematical concepts. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter.
Topics and features:- Provides an introduction to the basic notation and mathematical concepts for describing an image, and the key concepts for mapping an image into an image
- Explains the topologic and geometric basics for analysing image regions and distributions of image values, and discusses identifying patterns in an image
- Introduces optic flow for representing dense motion, and such topics in sparse motion analysis as keypoint detection and descriptor definition, and feature tracking using the Kalman filter
- Describes special approaches for image binarization and segmentation of still images or video frames
- Examines the three basic components of a computer vision system, namely camera geometry and photometry, coordinate systems, and camera calibration
- Reviews different techniques for vision-based 3D shape reconstruction, including the use of structured lighting, stereo vision, and shading-based shape understanding
- Includes a discussion of stereo matchers, and the phase-congruency model for image features
- Presents an introduction into classification and learning, with a detailed description of basic AdaBoost and the use of random forests
This concise and easy to read textbook/reference is ideal for an introductory course at third- or fourth-year level in an undergraduate computer science or engineering programme.
Most helpful customer reviews
15 of 16 people found the following review helpful.
probably the only textbook in the market for intro-level computer vision
By Turtleman
I took a computer vision class using Szeliski's book,
I was NOT satisfied to the book, so I searched around to find another textbook for learning & reference.
There are some other books in computer vision.
Szeliski...........: A literature review, NOT a textbook.
Forsyth & Ponce: A famous mess. Don't buy it.
Prince.............: Great book. geared toward recognition.
Davies............: Great book. geared toward image processing
Shapiro...........: Used to be Excellent intro-level book. Too outdated now.
Finally, I found this book.
This is probably the only textbook available in the market.
The topics are carefully selected, so that the book covers all essential topics in equally balanced manner.
The explanation is very clear in most parts.
Excellent intro-level book for learning & reference.
------------------------------------------
P.S. changed my review on Prince's and Davies' book.
4 of 4 people found the following review helpful.
Succinct Exposition of Computer Vision
By Shanmuga
I have been teaching computer vision for the past 2 years. There was definitely a dire need for an undergraduate textbook for computer vision. Existing books are more research oriented and not that suitable for classroom use. This book has contents which are succinctly explained and the breadth of topics covered is amazing. This book would best serve the purpose for a first course in computer vision. The important feature I liked about this book is the coverage of state-of-the-art algorithms in computer vision without compromising on the lucidity. I reckon this book would be adopted for various computer vision courses in near future. I also plan to adopt this book for my next offering of computer vision.
4 of 4 people found the following review helpful.
Clear and concise! Great book!
By Jona
It is a great book on a difficult topic. It covers all the main topics an undergrad course in vision would cover. Provides insight and detailed descriptions of classical and modern methods. I really liked the detailed overview on Viola's method, and a great explanation on Adaboost.
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