Active Computer Vision by Cooperative Focus and Stereo
This book addresses an area of perception engineering which deals with constructive processes. A model of the environment is analyzed using the information acquired from mUltiple viewpoints of multiple disparate sensors at multiple time instants. Although the role of successive model building and active exploration of the environment, as is discussed in this book, is of great importance, only a few researchers of machine perception have thus far addressed the problem in these directions. Krotkov's book, which is a modification and continuation of his highly successful dissertation, focuses on active exploratory sensing in the context of spatial layout perception. He uses stereo and focus to obtain distance By information, and to eventually develop cooperative combining techniques. means of a stereo system with verging cameras, it is demonstrated that the distance measurements can be significantly improved by combining two sources. In addition, the problem of merging information from the multiple views is discussed in detail. As the field of perception engineering seems to be of growing scientific and applied importance, both practitioners and researchers in machine perception will find this book a valuable addition to their libraries. RameshJain Series Editor Acknowledgements I would like to thank Professor Ruzena Bajcsy for her constant encouragement and guidance during the five years of research leading to the dissertation upon which this book is based. Without her help in all matters, this work would never have been possible.
1136530432
Active Computer Vision by Cooperative Focus and Stereo
This book addresses an area of perception engineering which deals with constructive processes. A model of the environment is analyzed using the information acquired from mUltiple viewpoints of multiple disparate sensors at multiple time instants. Although the role of successive model building and active exploration of the environment, as is discussed in this book, is of great importance, only a few researchers of machine perception have thus far addressed the problem in these directions. Krotkov's book, which is a modification and continuation of his highly successful dissertation, focuses on active exploratory sensing in the context of spatial layout perception. He uses stereo and focus to obtain distance By information, and to eventually develop cooperative combining techniques. means of a stereo system with verging cameras, it is demonstrated that the distance measurements can be significantly improved by combining two sources. In addition, the problem of merging information from the multiple views is discussed in detail. As the field of perception engineering seems to be of growing scientific and applied importance, both practitioners and researchers in machine perception will find this book a valuable addition to their libraries. RameshJain Series Editor Acknowledgements I would like to thank Professor Ruzena Bajcsy for her constant encouragement and guidance during the five years of research leading to the dissertation upon which this book is based. Without her help in all matters, this work would never have been possible.
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Active Computer Vision by Cooperative Focus and Stereo

Active Computer Vision by Cooperative Focus and Stereo

by Eric P. Krotkov
Active Computer Vision by Cooperative Focus and Stereo

Active Computer Vision by Cooperative Focus and Stereo

by Eric P. Krotkov

Paperback(Softcover reprint of the original 1st ed. 1989)

$109.99 
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Overview

This book addresses an area of perception engineering which deals with constructive processes. A model of the environment is analyzed using the information acquired from mUltiple viewpoints of multiple disparate sensors at multiple time instants. Although the role of successive model building and active exploration of the environment, as is discussed in this book, is of great importance, only a few researchers of machine perception have thus far addressed the problem in these directions. Krotkov's book, which is a modification and continuation of his highly successful dissertation, focuses on active exploratory sensing in the context of spatial layout perception. He uses stereo and focus to obtain distance By information, and to eventually develop cooperative combining techniques. means of a stereo system with verging cameras, it is demonstrated that the distance measurements can be significantly improved by combining two sources. In addition, the problem of merging information from the multiple views is discussed in detail. As the field of perception engineering seems to be of growing scientific and applied importance, both practitioners and researchers in machine perception will find this book a valuable addition to their libraries. RameshJain Series Editor Acknowledgements I would like to thank Professor Ruzena Bajcsy for her constant encouragement and guidance during the five years of research leading to the dissertation upon which this book is based. Without her help in all matters, this work would never have been possible.

Product Details

ISBN-13: 9781461396659
Publisher: Springer New York
Publication date: 12/01/2011
Series: Springer Series in Perception Engineering
Edition description: Softcover reprint of the original 1st ed. 1989
Pages: 160
Product dimensions: 6.10(w) x 9.25(h) x 0.01(d)

Table of Contents

1 Introduction.- 1.1 Active Exploratory Sensing.- 1.2 Research Domain.- 1.3 Overview.- 2 An Agile Stereo Camera System.- 2.1 Camera System Hardware.- 2.2 Device Controllers.- 2.3 Discussion.- 3 Focus Ranging.- 3.1 Analysis of Defocus.- 3.2 Criterion Functions Measuring Focus Quality.- 3.3 Criterion Function Implementation and Evaluation.- 3.4 Search for Criterion Function Maximum.- 3.5 Computing Range from Focusing.- 3.6 Discussion.- 4 Stereo with Verging Cameras.- 4.1 Computing Stereo Disparities.- 4.2 Computing Range using Calibrated Stereo Disparities.- 4.3 Error Analysis.- 4.4 Experimental Results.- 4.5 Discussion.- 5 Cooperative Ranging.- 5.1 Cooperative Focusing and Stereo.- 5.2 Integration Policy.- 5.3 Experimental Results.- 5.4 Discussion.- 6 Merging Multiple Uncertain Views.- 6.1 Problem Definition and Solution Approaches.- 6.2 Transformation Parameters.- 6.3 Object Location Uncertainty.- 6.4 Transformed Locations.- 6.5 Experimental Results.- 6.6 Discussion.- 7 Modeling Sparse Range Data.- 7.1 Model Primitives.- 7.2 Clustering.- 7.3 Object-Oriented Representation.- 7.4 Results.- 7.5 Discussion.- 8 Conclusion.- 8.1 Review.- 8.2 Extensions.- 8.3 Connections.- 8.4 Synopsis.- Appendix I Object Position and Disparity.- Appendix II Calibration Procedures.- II.1 Aperture.- I1.2 Zoom.- II.3 Focus.- I1.4 Vergence.- 1I.5 Platform.- II.6 Discussion.- References.
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