An Invitation to 3-D Vision.pdf三维重建，高清，且完整。Interdi

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详细说明：三维重建，高清，且完整。Interdisciplinary Applied Mathematics Volumes published are listed at the end of this book. Springer Science+ Business Media, LLC An invitation to 3-d vision From Images to Geometric Models Yi Ma Stefano soatto Jana Kosecka s. Shankar Sastry With 170 Illustrations Springer Science+Business media, LLC Yi Ma Stefano soatto Department of Electrical and Department of Computer Science Computer Engineering University of California, Los Angeles University of Illinois at Los Angeles, CA 90095 Urbana-Champaign USA Urbana, IL 61801 soattoucla. edu USA yimauiuc. edu Jana Kosecka S. Shankar Sastry Department of Computer Science Department of Electrical Engineering George Mason University and Computer Science Fairfax, VA 22030 University of California, Berkeley USA Berkeley, CA 94720 koseckacs gmu. edu USA sastry eecs. berkeley. edu Editors S.S. Antman J E. Marsden Department of mathematics Control and Dynamical Systems and Mail Code 107-81 Institute for Physical Science Califomia Institute of Technology and Technolo Pasadena, CA 91125 University of Maryland USA College Park, MD 20742 marsden cds. caltech. edu USA ssamath. umd. edu L Sirovich S. wiggins Division of Applied Mathematics School of mathematics Brown University University of Bristol Providence, RI 02912 Bristol BS8 ITW USA UK chico camelot. mssm. edu swigginsbris ac uk Cover Illustration:AXo-GJ"1968(180 x 180 cm) by Victor Vasarely. Copyright Michele Vasarel Mathematics Subject Classification(2000): 51U10, 68U10, 65D18 SBN978-l-449-846-8 SBN978-0-387-21779-6( cOok) DoII0.1007/978-0-387-217796 Printed on acid-free paper 2004 Springer Science+Business Media New York Originally published by Springer-Verlag New York, Inc in 2004 Softcover reprint of the hardcover Ist edition 2004 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher, (Springer Science+ Business Media New York) except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary 98765432 (EB) springeronline.com To my mother and my father (r.M) To Giuseppe Torresin, Engineer(SS To my parents(JK) To my mother(SSS reface This book is intended to give students at the advanced undergraduate or introduc- tory graduate level, and researchers in computer vision robotics and computer graphics, a self-contained introduction to the geometry of three-dimensional (3 D)vision. This is the study of the reconstruction of 3-D models of objects from a collection of 2-D images. An essential prerequisite for this book is a course in linear algebra at the advanced undergraduate level. Background knowledge igid-body motion, estimation and optimization will certainly improve the reader's appreciation of the material but is not critical since the first few chapters and the appendices provide a review and summary of basic notions and results on these topics Our motivation Research monographs and books on geometric approaches to computer vision have been published recently in two batches: The first was in the mid 1990s with books on the geometry of two views, see e.g. [Faugeras, 1993, Kanatani, 1993b Maybank, 1993, Weng et al., 1993b]. The second was more recent with books fo cusing on the geometry of multiple views, see e.g. [Hartley and Zisserman, 2000 and [Faugeras and Luong, 2001] as well as a more comprehensive book on computer vision [Forsyth and Ponce, 2002]. We felt that the time was ripe for synthesizing the material in a unified framework so as to provide a self-contained exposition of this subject, which can be used both for pedagogical purposes and by practitioners interested in this field. Although the approach we take in this book deviates from several other classical approaches, the techniques we use are mainly linear algebra and our book gives a comprehensive view of what is known Ⅴ iii Preface to date on the geometry of 3-d vision It also develops homogeneous terminology on a solid analytical foundation to enable what should be a great deal of future research in this young field Apart from a self-contained treatment of geometry and algebra associated with computer vision, the book covers relevant aspects of the image formation process basic image processing, and feature extraction techniques-essentially all that one needs to know in order to build a system that can automatically generate a 3-D model from a set of 2-D images Organization of the book This book is organized as follows: Following a brief introduction, Part I provides background material for the rest of the book. Two fundamental transformations in multiple-view geometry, namely, rigid-body motion and perspective projec tion, are introduced in Chapters 2 and 3, respectively. Feature extraction and correspondence are discussed in Chapter 4 Chapters 5, 6, and 7, in Part Il, cover the classic theory of two-view geometry based on the so-called epipolar constraint. Theory and algorithms are developed for both discrete and continuous motions, both general and planar scenes, both calibrated and uncalibrated camera models, and both single and multiple moving objects. Although the epipolar constraint has been very successful in the two-view case, Part Ill shows that a more proper tool for studying the geometry of multiple views is the so-called rank condition on the multiple-view matrix( Chapter 8), which uni fies all the constraints among multiple images that are known to date The theory culminates in Chapter 9 with a unified theorem on a rank condition for arbitrarily mixed point, line, and plane features. It captures all possible constraints among multiple images of these geometric primitives, and serves as a key to both geomet ric analysis and algorithmic development. Chapter 10 uses the rank condition to reexamine and unify the study of single-view and multiple-view geometry given scene knowledge such as symmetry Based on the theory and conceptual algorithms developed in the early part of the book, Chapters 11 and 12, in Part IV, demonstrate practical reconstruction algorithms step-by-step, as well as discuss possible extensions of the theory cov ered in this book. An outline of the logical dependency among chapters is given in Figure 1 Curriculum options Drafts of this book and the exercises in it have been used to teach a one-semester course at the university of California at berkeley the university of illinois at Urbana-Champaign, Washington University in St. Louis, the george Mason University and the University of Pennsylvania, and a one-quarter course at the University of California at Los Angeles. There is apparently adequate material for two semesters or three quarters of lectures. Advanced topics suggested in Part IV or chosen by the instructor can be added to the second half of the sec Preface A Part I ch. 2 ch 3 h.4 ch. 5 Part II h.6 ch. 7 Part Ill ch ch. 9 ch.10 ch.12 Figure 1. Organization of the book: logical dependency among parts and chapters ond semester if a two-semester course is offered. Below are some suggestions for course development based on this book 1. A one-semester course: Appendix A, Chapters 1-6, and part of Chapters 8-10 2. A two-quarter course: Chapters 1-6 for the first quarter, and Chapters 8-10, 12 for the second quarter 3. A two-semester course: Appendix A and Chapters 1-6 for the first semester Chapters 7-10 and the instructors choice of some advanced topics from Chapter 12 for the second semester 4. A three-quarter sequence: Chapters 1-6 for the first quarter, Chapters 7-10 projects from Chapters 11 and 12 for the third quarter dvanced topics and or the second quarter, and the instructors choice of Chapter 1l plays a special role in this book: Its purpose is to make it easy for the instructor to develop and assign experimental exercises or course projects along with other chapters being taught throughout the course. Relevant code is available Preface athttp://vision.ucla.edu/masks,fromwhichstudentsmaygethands on experience with a minimum version of a working computer vision system This chapter can also be used by practitioners who are interested in using the algorithms developed in this book, without necessarily delving into the details of the mathematical formulation. Finally, an additional purpose of this chapter is to summarize "the book in one chapter which can be used in the first lecture as an overview of what is to come Exercises are provided at the end of each chapter They consist of mainly three 1. drill exercises that help students understand the theory covered in each chapter 2. advanced exercises that guide students to creatively develop a solution to a specialized case that is related to but not necessarily covered by the general theorems in the book 3. programming exercises that help students grasp the algorithms developed n each chapter Solutions to selected exercises are available, along with software for examples andalgorithmsathttp://vision.ucla.edu/masks Yi Ma, Champaign, Illinois Stefano Soatto, Los Angeles, California Jana Kosecka, Fairfax, virginia Shankar Sastry, Berkeley, California S 2003

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