Title:
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Graph matching using SIFT descriptors: an application to pose recovery of a mobile robot
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Author:
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Sanromà Güell, Gerard; Alquézar Mancho, René; Serratosa Casanelles, Francesc
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics; Universitat Politècnica de Catalunya. SOCO - Soft Computing |
Abstract:
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Image-feature matching based on Local Invariant Feature Extraction (LIFE) methods has proven to be successful, and SIFT is one of the most effective. SIFT matching uses only local texture information to compute the correspondences. A number of approaches have been presented aimed at enhancing the image-features matches computed using only local information such as SIFT. What most of these approaches have in common is that they use a higher level information such as spatial arrangement of the feature points to reject a subset of outliers. The main limitation of the outlier rejectors is that they are not able to enhance the configuration of matches by adding new useful ones. In the present work we propose a graph matching algorithm aimed not only at rejecting erroneous matches but also at selecting additional useful ones. We use both the graph structure to encode the geometrical information and the SIFT descriptors in the node’s attributes to provide local texture information. This algorithm is an ensemble of successful ideas previously reported by other researchers. We demonstrate the effectiveness of our algorithm in a pose recovery application. |
Abstract:
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Peer Reviewed |
Subject(s):
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-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes -Pattern recognition systems -image recognition
mobile robots
pattern recognition
robot vision -Reconeixement de formes (Informàtica) -Classificació INSPEC::Pattern recognition::Object recognition |
Rights:
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Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Document type:
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Article - Published version Conference Object |
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