The Maximum Consensus Problem

丛 书 名：Synthesis Lectures on Computer Vision

版本说明：1

作     者：Tat-Jun Chin David Suter 

I S B N：(纸本) 9783031006906 

出 版 社：Springer Cham 

出 版 年：1000年

页      数：XV, 178页

主 题 词：Computer Imaging, Vision, Pattern Recognition and Graphics Image Processing and Computer Vision Pattern Recognition 

摘      要：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;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.