Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.21/5068
Título: Global localization with non-quantized local image features
Autor: Campos, Francisco M.
Correia, Luís
Calado, João Manuel Ferreira
Palavras-chave: Topological Localization
Appearance-Based Methods
Feature Selection
Information Content
Texture Classification
Omnidirectional Images
Markov Localization
Robot Localization
Binary Patterns
Mobile Robots
Data: Ago-2012
Editora: Elsevier Science BV
Citação: CAMPOS, F. M.; CORREIA, L.; CALADO, J. M. F. – Global localization with non-quantized local image features. Robotics and Autonomous Systems. ISSN: 0921-8890. Vol. 60, nr. 8 (2012), pp. 1011-1020
Resumo: In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.
Peer review: yes
URI: http://hdl.handle.net/10400.21/5068
DOI: 10.1016/j.robot.2012.05.015
ISSN: 0921-8890
Aparece nas colecções:ISEL - Eng. Mecan. - Artigos

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