Panoramic Vision

1. Front Matter

   Pages i-xxiv

   PDF

2. Introduction

   1. Introduction

      • R. Benosman, S. B. Kang

      Pages 1-4

3. A Brief Historical Perspective on Panorama

   1. A Brief Historical Perspective on Panorama

      • R. Benosman, S. B. Kang

      Pages 5-20

4. Catadioptric Panoramic Systems

   1. Front Matter

      Pages 21-22

      PDF

   2. Development of Low-Cost Compact Omnidirectional Vision Sensors

      • H. Ishiguro

      Pages 23-38

   3. Single Viewpoint Catadioptric Cameras

      • S. Baker, S. K. Nayar

      Pages 39-71

   4. Epipolar Geometry of Central Panoramic Catadioptric Cameras

      • T. Pajdla, T. Svoboda, V. Hlaváč

      Pages 73-102

   5. Folded Catadioptric Cameras

      • S. K. Nayar, V. Peri

      Pages 103-119

5. Panoramic Stereo Vision Systems

   1. Front Matter

      Pages 121-122

      PDF

   2. A Real-time Panoramic Stereo Imaging System and Its Applications

      • A. Basu, J. Baldwin

      Pages 123-141

   3. Panoramic Imaging with Horizontal Stereo

      • S. Peleg, M. Ben-Ezra, Y. Pritch

      Pages 143-160

   4. Panoramic Stereovision Sensor

      • R. Benosman, J. Devars

      Pages 161-168

   5. Calibration of the Stereovision Panoramic Sensor

      • R. Benosman, J. Devars

      Pages 169-180

   6. Matching Linear Stereoscopic Images

      • R. Benosman, J. Devars

      Pages 181-199

6. Techniques for Generating Panoramic Images

   1. Front Matter

      Pages 201-203

      PDF

   2. Characterization of Errors in Compositing Cylindrical Panoramic Images

      • S. B. Kang, R. Weiss

      Pages 205-226

   3. Construction of Panoramic Image Mosaics with Global and Local Alignment

      • H.-Y. Shum, R. Szeliski

      Pages 227-268

   4. Self-Calibration of Zooming Cameras from a Single Viewpoint

      • L. de Agapito, E. Hayman, I. D. Reid, R. I. Hartley

      Pages 269-289

   5. 360 x 360 Mosaics: Regular and Stereoscopic

      • S. K. Nayar, A. D. Karmarkar

      Pages 291-307

   6. Mosaicing with Strips on Adaptive Manifolds

      • S. Peleg, B. Rousso, A. Rav-Acha, A. Zomet

      Pages 309-325

Current cameras are poor imitations of the human eye and close descen­ dants in their design of ideas and a technology that are more than a century old. People in computer vision have traditionally used off-the-shelf cameras that were not meant for the uses they were intended for by these researchers: off-the-shelf cameras are designed to capture images to be printed on paper or looked at on a television screen, not for guiding robots or making 3D models of the environment or even surveilling a large area where very large field of views, high geometric and photometric accuracies are necessary. Quite a significant part of the efforts in computer vision has been targeted at overcoming algorithmically these problems. The authors of this book convince us that it is possible to abandon the traditional route of using standard cameras and to follow the path of designing new cameras explicitly for solving the tasks at hand in computer vision applications. This leads to different design concepts and allows to alleviate many of the difficulties encountered in the processing of the images taken with the "traditional" cameras.

• Epipolar geometry
• Stereo
• Tracking
• Vision Sensor
• calibration
• compositing
• computer vision
• imaging
• imaging techniques
• machine vision
• modeling
• multimedia
• robot
• robotics
• video

From the reviews:

"I first congratulate the authors for the efforts they have done to explain with great detail and easy language such a complex argument as panoramic vision. … This book is a good ‘database’ of arguments on theoretical and practical aspects of panoramic vision. In fact, both algorithmic and implementation items are treated with great accuracy … . The book has been written by many authors yet the chapters present homogeneity and good coordination in exposing different arguments." (Nello Balossino, The Computer Journal, Vol. 45 (6), 2002)

"This book presents the rebirth of panoramic vision as it is applied to computer vision. It focuses on the creation and analysis of images with fields of view that are much greater than those obtained from typical cameras. … Overall, this is an informative and coherent reference text that provides details of current research in this field. It is suitable for researchers and professionals involved with computer vision, virtual reality, teleconferencing, imaging systems, and robotics." (The Industrial Robot, Vol. 29 (2), 2002)

• Laboratoire des Instruments et Systems, University Pierre et Marie Curie, Paris cedex 05, France

  Ryad Benosman

• Microsoft Corporation, Redmond, USA

  Sing Bing Kang

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