Introductory Techniques For 3D Computer Vision Pdf Download Free

Introductory Techniques for 3-D Computer Vision
by Emanuele Trucco, Alessandro Verri

Senior/Graduate level courses on computer vision, robot vision and image processing in electrical and computer engineering, mathematics, and computer science departments, and an essential reference for researchers and scientists in the field of computer vision. An applied introduction to modern computer vision, focusing on a set of computational techniques for 3-D imaging. Covers a wide range of fundamental problems encountered within computer vision and provides detailed algorithmic and theoretical solutions for each. Each chapter concentrates on a specific problem and solves it by building on previous results.

An Introduction to 3D Computer Vision Techniques and Algorithms
by Boguslaw Cyganek, J. Paul Siebert

Computer vision encompasses the construction of integrated visionsystems and the application of vision to problems of real-worldimportance. The process of creating 3D models is still ratherdifficult, requiring mechanical measurement of the camera positionsor manual alignment of partial 3D views of a scene. However usingalgorithms, it is possible to take a collection of stereo-pairimages of a scene and then automatically produce a photo-realistic,geometrically accurate digital 3D model.

This book provides a comprehensive introduction to the methods,theories and algorithms of 3D computer vision. Almost everytheoretical issue is underpinned with practical implementation or aworking algorithm using pseudo-code and complete code written inC++ and MatLab®. There is the additional clarification of anaccompanying website with downloadable software, case studies andexercises. Organised in three parts, Cyganek and Siebert give abrief history of vision research, and subsequently:  

  • present basic low-level image processing operations for imagematching, including a separate chapter on image matchingalgorithms;
  • explain scale-space vision, as well as space reconstruction andmultiview integration;
  • demonstrate a variety of practical applications for 3D surfaceimaging and analysis;
  • provide concise appendices on topics such as the basics ofprojective geometry and tensor calculus for image processing,distortion and noise in images plus image warping procedures.

An Introduction to 3D Computer Vision Algorithms andTechniques is a valuable reference for practitioners andprogrammers working in 3D computer vision, image processing andanalysis as well as computer visualisation. It would also be ofinterest to advanced students and researchers in the fields ofengineering, computer science, clinical photography, robotics,graphics and mathematics.


An Invitation to 3-D Vision
by Yi Ma, Stefano Soatto, Jana Kosecká, S. Shankar Sastry

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 in rigid-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 aI. , 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.

Multiple View Geometry in Computer Vision
by Richard Hartley, Andrew Zisserman

A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.

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