Outlier-Robust Estimation: Hardness, Minimally Tuned Algorithms, and Applications

Nonlinear estimation in robotics and vision is typically plagued with outliers due to wrong data association or incorrect detections from signal processing and machine learning methods. This article introduces two unifying formulations for outlier-robust estimation, generalized maximum consensus (&l...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on robotics Ročník 38; číslo 1; s. 281 - 301
Hlavní autoři:	Antonante, Pasquale, Tzoumas, Vasileios, Yang, Heng, Carlone, Luca
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.02.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Adaptive algorithms Algorithms Approximation algorithms autonomous systems Combinatorial analysis computational complexity computer vision Estimation Formulations Inliers (landforms) Machine learning maximum likelihood estimation Measurement uncertainty Object recognition Optimization Outliers (statistics) Particle measurements Polynomials Probabilistic logic resilient perception Robotics robust estimation Robustness Signal processing Signal processing algorithms Simultaneous localization and mapping
ISSN:	1552-3098, 1941-0468
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!