Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.21/3831
Título: An Evaluation of Local Feature Combiners for Robot Visual Localization
Autor: Campos, Francisco M.
Correia, Luis
Calado, João Manuel Ferreira
Palavras-chave: Robot visual Localization
Information Fusion
Multiple Classifier Systems
Data: 2013
Editora: IEEE
Citação: CAMPOS, Francisco M.; CORREIA, Luis; CALADO, João M. F. - An Evaluation of Local Feature Combiners for Robot Visual Localization. 13th International Conference on Autonomous Robot Systems (ROBOTICA). (2013).
Resumo: In the last decade, local image features have been widely used in robot visual localization. To assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image to those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, we compare several candidate combiners with respect to their performance in the visual localization task. A deeper insight into the potential of the sum and product combiners is provided by testing two extensions of these algebraic rules: threshold and weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance. The voting method, whilst competitive to the algebraic rules in their standard form, is shown to be outperformed by both their modified versions.
Peer review: yes
URI: http://hdl.handle.net/10400.21/3831
ISBN: 978-1-4799-1247-6
978-1-4799-1246-9
Versão do Editor: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6623526
Aparece nas colecções:ISEL - Eng. Mecan. - Artigos

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