An Invitation to 3-D Vision: From Images to Geometric Models (Interdisciplinary Applied Mathematics (26))

Ma, Yi; Soatto, Stefano; Kosecká, Jana; Sastry, S. Shankar

ISBN 10: 0387008934 / ISBN 13: 9780387008936

Editore: Springer, 2004

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CLEAN Fine 2004 hardcover. Appears unused.

Codice articolo 045105

Dati bibliografici

• Titolo: An Invitation to 3-D Vision: From Images to Geometric Models (Interdisciplinary Applied Mathematics (26))
• Editore: Springer
• Data di pubblicazione: 2004
• Lingua: Inglese
• ISBN 10: 0387008934
• ISBN 13: 9780387008936
• Rilegatura: Hardcover
• Edizione: seconda edizione
• Condizione: Fine
• Condizione della sovraccoperta: No Jacket as Issued

Descrizione articolo

Riassunto

This book gives senior undergraduate and beginning graduate students and researchers in computer vision, applied mathematics, computer graphics, and robotics a self-contained introduction to the geometry of 3D vision; that is the reconstruction of 3D models of objects from a collection of 2D images. Following a brief introduction, Part I provides background materials for the rest of the book. The two fundamental transformations, namely rigid body motion and perspective projection are introduced and image formation and feature extraction discussed. Part II covers the classic theory of two view geometry based on the so-called epipolar constraint. Part III shows that a more proper tool for studying the geometry of multiple views is the so- called rank considtion on the multiple view matrix. Part IV develops practical reconstruction algorithms step by step as well as discusses possible extensions of the theory. Exercises are provided at the end of each chapter. Software for examples and algorithms are available on the author's website.

Dalla quarta di copertina

Endowing machines with a sense of vision has been a dream of scientists and engineers alike for over half a century. Only in the past decade, however, has the geometry of vision been understood to the point where this dream becomes attainable, thanks also to the remarkable progress in imaging and computing hardware.

This book addresses a central problem in computer vision -- how to recover 3-D structure and motion from a collection of 2-D images -- using techniques drawn mainly from linear algebra and matrix theory. The stress is on developing a unified framework for studying the geometry of multiple images of a 3-D scene and reconstructing geometric models from those images. The book also covers relevant aspects of image formation, basic image processing, and feature extraction. The authors bridge the gap between theory and practice by providing step-by-step instructions for the implementation of working vision algorithms and systems.

Written primarily as a textbook, the aim of this book is to give senior undergraduate and beginning graduate students in computer vision, robotics, and computer graphics a solid theoretical and algorithmic foundation for future research in this burgeoning field. It is entirely self-contained with necessary background material covered in the beginning chapters and appendices, and plenty of exercises, examples, and illustrations given throughout the text.