The Maximum Consensus Problem (Record no. 84914)
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000 -LEADER | |
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fixed length control field | 03241nam a22005295i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-031-01818-3 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20240730163724.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 220601s2017 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783031018183 |
-- | 978-3-031-01818-3 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006 |
100 1# - AUTHOR NAME | |
Author | Chin, Tat-Jun. |
245 14 - TITLE STATEMENT | |
Title | The Maximum Consensus Problem |
Sub Title | Recent Algorithmic Advances / |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2017. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XV, 178 p. |
490 1# - SERIES STATEMENT | |
Series statement | Synthesis Lectures on Computer Vision, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | Preface -- Acknowledgments -- The Maximum Consensus Problem -- Approximate Algorithms -- Exact Algorithms -- Preprocessing for Maximum Consensus -- Appendix -- Bibliography -- Authors' Biographies -- Index . |
520 ## - SUMMARY, ETC. | |
Summary, etc | Outlier-contaminated data is a fact of life in computer vision. For computer vision applications to perform reliably and accurately in practical settings, the processing of the input data must be conducted in a robust manner. In this context, the maximum consensus robust criterion plays a critical role by allowing the quantity of interest to be estimated from noisy and outlier-prone visual measurements. The maximum consensus problem refers to the problem of optimizing the quantity of interest according to the maximum consensus criterion. This book provides an overview of the algorithms for performing this optimization. The emphasis is on the basic operation or "inner workings" of the algorithms, and on their mathematical characteristics in terms of optimality and efficiency. The applicability of the techniques to common computer vision tasks is also highlighted. By collecting existing techniques in a single article, this book aims to trigger further developments in this theoretically interesting and practically important area. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
General subdivision | Digital techniques. |
700 1# - AUTHOR 2 | |
Author 2 | Suter, David. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://doi.org/10.1007/978-3-031-01818-3 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
-- | Cham : |
-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2017. |
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-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
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-- | online resource |
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-- | text file |
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-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Image processing |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer vision. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Pattern recognition systems. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer Imaging, Vision, Pattern Recognition and Graphics. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer Vision. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Automated Pattern Recognition. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 2153-1064 |
912 ## - | |
-- | ZDB-2-SXSC |
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