Share
The Maximum Consensus Problem: Recent Algorithmic Advances
David Suter
(Author)
·
Tat-Jun Chin
(Author)
·
Springer
· Paperback
The Maximum Consensus Problem: Recent Algorithmic Advances - Chin, Tat-Jun ; Suter, David
£ 57.84
£ 64.27
You save: £ 6.43
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My WishlistsIt will be shipped from our warehouse between
Monday, July 22 and
Tuesday, July 23.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.
Synopsis "The Maximum Consensus Problem: Recent Algorithmic Advances"
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.
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
✓ Producto agregado correctamente al carro, Ir a Pagar.
