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  • 标题:Efficient Topological Localization Using Global and Local Feature Matching
  • 作者:Junqiu Wang ; Yasushi Yagi
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2013
  • 卷号:10
  • 期号:3
  • 页码:153
  • DOI:10.5772/55630
  • 语种:English
  • 出版社:SAGE Publications
  • 摘要:We present an efficient vision-based global topological localization approach in which different image features are used in a coarse-to-fine matching framework. Orientation Adjacency Coherence Histogram (OACH), a novel image feature, is proposed to improve the coarse localization. The coarse localization results are taken as inputs for the fine localization which is carried out by matching Harris-Laplace interest points characterized by the SIFT descriptor. The computation of OACHs and interest points is efficient due to the fact that these features are computed in an integrated process. The matching of local features is improved by using approximate nearest neighbor searching technique. We have implemented and tested the localization system in real environments. The experimental results demonstrate that our approach is efficient and reliable in both indoor and outdoor environments. This work has also been compared with previous works. The comparison results show that our approach has better performance with higher correct ratio and lower computational complexity.
  • 关键词:A Localization; Global Features; Local Features; Feature Matching
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