Time-of-Flight Cameras: Principles, Methods and Applications

Springer Science & Business Media
4
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Time-of-flight (TOF) cameras provide a depth value at each pixel, from which the 3D structure of the scene can be estimated. This new type of active sensor makes it possible to go beyond traditional 2D image processing, directly to depth-based and 3D scene processing. Many computer vision and graphics applications can benefit from TOF data, including 3D reconstruction, activity and gesture recognition, motion capture and face detection. It is already possible to use multiple TOF cameras, in order to increase the scene coverage, and to combine the depth data with images from several colour cameras. Mixed TOF and colour systems can be used for computational photography, including full 3D scene modelling, as well as for illumination and depth-of-field manipulations. This work is a technical introduction to TOF sensors, from architectural and design issues, to selected image processing and computer vision methods.
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Additional Information

Publisher
Springer Science & Business Media
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Published on
Nov 6, 2012
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Pages
96
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ISBN
9781447146582
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Best For
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Language
English
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Genres
Computers / Computer Graphics
Computers / Optical Data Processing
Computers / Software Development & Engineering / General
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Content Protection
This content is DRM protected.
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55% new material in the latest edition of this “must-have for students and practitioners of image & video processing!

This Handbook is intended to serve as the basic reference point on image and video processing, in the field, in the research laboratory, and in the classroom. Each chapter has been written by carefully selected, distinguished experts specializing in that topic and carefully reviewed by the Editor, Al Bovik, ensuring that the greatest depth of understanding be communicated to the reader. Coverage includes introductory, intermediate and advanced topics and as such, this book serves equally well as classroom textbook as reference resource.

• Provides practicing engineers and students with a highly accessible resource for learning and using image/video processing theory and algorithms
• Includes a new chapter on image processing education, which should prove invaluable for those developing or modifying their curricula
• Covers the various image and video processing standards that exist and are emerging, driving today’s explosive industry
• Offers an understanding of what images are, how they are modeled, and gives an introduction to how they are perceived
• Introduces the necessary, practical background to allow engineering students to acquire and process their own digital image or video data
• Culminates with a diverse set of applications chapters, covered in sufficient depth to serve as extensible models to the reader’s own potential applications

About the Editor...
Al Bovik is the Cullen Trust for Higher Education Endowed Professor at The University of Texas at Austin, where he is the Director of the Laboratory for Image and Video Engineering (LIVE). He has published over 400 technical articles in the general area of image and video processing and holds two U.S. patents. Dr. Bovik was Distinguished Lecturer of the IEEE Signal Processing Society (2000), received the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millennium Medal (2000), and twice was a two-time Honorable Mention winner of the international Pattern Recognition Society Award. He is a Fellow of the IEEE, was Editor-in-Chief, of the IEEE Transactions on Image Processing (1996-2002), has served on and continues to serve on many other professional boards and panels, and was the Founding General Chairman of the IEEE International Conference on Image Processing which was held in Austin, Texas in 1994.

* No other resource for image and video processing contains the same breadth of up-to-date coverage
* Each chapter written by one or several of the top experts working in that area
* Includes all essential mathematics, techniques, and algorithms for every type of image and video processing used by electrical engineers, computer scientists, internet developers, bioengineers, and scientists in various,
image-intensive disciplines
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