Geometric Properties for Incomplete Data: 31 (Computational Imaging and Vision) - Softcover

 
9789048169825: Geometric Properties for Incomplete Data: 31 (Computational Imaging and Vision)

Inhaltsangabe

Computer vision and image analysis require interdisciplinary collaboration between mathematics and engineering. This book addresses the area of high-accuracy measurements of length, curvature, motion parameters and other geometrical quantities from acquired image data. It is a common problem that these measurements are incomplete or noisy, such that considerable efforts are necessary to regularise the data, to fill in missing information, and to judge the accuracy and reliability of these results. This monograph brings together contributions from researchers in computer vision, engineering and mathematics who are working in this area.

The book can be read both by specialists and graduate students in computer science, electrical engineering or mathematics who take an interest in data evaluations by approximation or interpolation, in particular data obtained in an image analysis context.

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Críticas

From the reviews:

"This compendium should be treated as a higher-level text with the target audience being computer scientists, electrical engineers, and mathematician, both in the research and industrial settings. Graduate-level students interested in pursuing advanced treatments of the topic can benefit from reading this book as well. ... This text is an important and worthwhile contribution to the computational imaging and vision literature; it is easy to read and rigorous in its mathematical development." (R. Goldberg, ACM Computing Reviews, Vol. 49 (4), April, 2008)

Reseña del editor

Computer vision and image analysis require interdisciplinary collaboration between mathematics and engineering. This book addresses the area of high-accuracy measurements of length, curvature, motion parameters and other geometrical quantities from acquired image data. It is a common problem that these measurements are incomplete or noisy, such that considerable efforts are necessary to regularise the data, to fill in missing information, and to judge the accuracy and reliability of these results. This monograph brings together contributions from researchers in computer vision, engineering and mathematics who are working in this area.

The book can be read both by specialists and graduate students in computer science, electrical engineering or mathematics who take an interest in data evaluations by approximation or interpolation, in particular data obtained in an image analysis context.

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Weitere beliebte Ausgaben desselben Titels

9781402038570: Geometric Properties for Incomplete Data: 31 (Computational Imaging and Vision)

Vorgestellte Ausgabe

ISBN 10:  1402038577 ISBN 13:  9781402038570
Verlag: Springer, 2005
Hardcover