Mohlo by se vám také líbit

Informovat o naskladnění knihy

Více informací o knize The Maximum Consensus Problem

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 85 bodů

Anotace knihy

This book provides an overview of the algorithms used for solving the maximum consensus problem. This problem solves the issues by extracting visual information from noisy and outlier-prone visual measurements. 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. The book discusses how the maximum consensus robust criterion plays a critical role. Moreover, the authors explain the various features of the algorithms used to solve this problem, as well as the mathematical characteristics of algorithms in terms of optimality and efficiency. The book also highlights the applications of the techniques for common computer vision tasks. This timely Second Edition incorporates many recent theoretical and practical advances since publication of the prior edition, collects existing techniques into one comprehensive resource, and encourages readers to pursue further research and developments in this area.

Parametry knihy

• Plný název: The Maximum Consensus Problem
• Podnázev: Recent Algorithmic Advances.DE
• Autor: Tat-Jun Chin, David Suter
• Edice: Synthesis Lectures on Computer Vision,
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 230
• EAN: 9783032473127
• ID: 54405782
• Nakladatelství: Springer, Berlin
• Rozměry: 240 × 168 mm
• Datum vydání: 03. May 2027

---

---

---