Evolutionary agent-based estimation of trifocal tensor for medical images

Autor:	MX Hu, Baozong Yuan, G. Dodds
Rok vydání:	2004
Předmět:	Theoretical computer science Trifocal tensor Computer science Noise (video) Tensor Electrical and Electronic Engineering Space (mathematics) Computational geometry Algorithm
Zdroj:	Electronics Letters. 40:523
ISSN:	0013-5194
DOI:	10.1049/el:20040365
Popis:	A novel estimation of a trifocal tensor based on evolutionary agents is presented. Each agent denotes a minimum subset for computing trilinear geometry and evolves autonomously in the vast solution space to obtain the optimal result. Experiments with medical images show that our approach is faster and more precise, and robust to noise and outliers.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::4d99b61a687211477ea2e8b49c728dff https://doi.org/10.1049/el:20040365 Zobrazit plný text záznamu