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- Title: Computer Vision: Algorithms and Applications
- Author(s) Richard Szeliski
- Publisher: Springer; 2011th edition (October 19, 2010); eBook (Draft, September 3, 2010)
- Permission: This electronic draft is for non-commercial personal use only, and may not be posted or re-distributed in any form.
- Hardcover: 832 pages
- eBook: PDF (979 pages, 22.1 MB)
- Language: English, Chinese, and Japanese
- ISBN-10: 1848829345
- ISBN-13: 978-1848829343
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As humans, we perceive the three-dimensional structure of the world around us with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem, and what is the current state of the art?
Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging and fun consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.
More than just a source of "recipes", this text/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting this process to produce the best possible descriptions of a scene. Exercises are presented throughout the book, with a heavy emphasis on testing algorithms.
Suitable for either an undergraduate or a graduate-level course in computer vision, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries.
About the Authors-
Dr. Richard Szeliski has over twenty years' experience in computer vision research, most notably at Digital Equipment Corporation and Microsoft.
- Computer Vision, Machine Vision, and Deep Learning
- Deep Learning and Neural Networks
- Digital Signal Processing (DSP), Sound and Imaging Processing
- Computer Graphics and Digital Images
- Artificial Intelligence, Machine Learning, and Logic Programming

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