Könyv Maximum Consensus Problem Tat-Jun Chin

Maximum Consensus Problem

Recent Algorithmic Advances

Szerző: Tat-Jun Chin
Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
19 596 Ft
Outlier-contaminated data is a fact of life in computer vision. For computer vision applications to...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2017
oldal
178
EAN
9783031006906
ISBN
3031006909
Enbook ID
39298258
Súly
380
Méretek
191 x 235 x 11

Teljes leírás

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.

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