Bayesian models for finding and grouping junctions
| Contribuinte(s) |
Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial Robótica y Visión Tridimensional (RoViT) Laboratorio de Investigación en Visión Móvil (MVRLab) Informática Industrial e Inteligencia Artificial |
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| Data(s) |
13/07/2012
13/07/2012
1999
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| Resumo |
In this paper, we propose two Bayesian methods for detecting and grouping junctions. Our junction detection method evolves from the Kona approach, and it is based on a competitive greedy procedure inspired in the region competition method. Then, junction grouping is accomplished by finding connecting paths between pairs of junctions. Path searching is performed by applying a Bayesian A* algorithm that has been recently proposed. Both methods are efficient and robust, and they are tested with synthetic and real images. |
| Identificador |
CAZORLA, M.A., et al. "Bayesian models for finding and grouping junctions". En: Energy Minimization Methods in Computer Vision and Pattern Recognition : Second International Workshop, EMMCVPR’99 York, UK, July 26–29, 1999 Proceedings / Edwin R. Hancock, Marcello Pelillo (Eds.). Berlin : Springer, 1999. (Lecture Notes in Computer Science; 1654). ISBN 3-540-66294-4, pp. 70-82 3-540-66294-4 0302-9743 (Print) 1611-3349 (Online) http://hdl.handle.net/10045/23398 10.1007/3-540-48432-9_6 |
| Idioma(s) |
eng |
| Publicador |
Springer Berlin / Heidelberg |
| Relação |
http://dx.doi.org/10.1007/3-540-48432-9_6 |
| Direitos |
The original publication is available at www.springerlink.com info:eu-repo/semantics/restrictedAccess |
| Palavras-Chave | #Bayesian methods #Junction detection #Junction grouping #Ciencia de la Computación e Inteligencia Artificial |
| Tipo |
info:eu-repo/semantics/conferenceObject |
