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- W2849573857 abstract "In this paper, we present a novel sequential visual localization algorithm in partitioned route. The algorithm utilizes Monte-Carlo for accurate visual localization. Partitioning the route into several regions produces higher accuracy along with lower computational cost. Each of the regions is represented using independent maps. We use bag-of-words for visual mapping of the environment. In addition, it shows smooth transition when the robot moves from one region to another. Experiments are carried out using data collected from crowded roads. Results show that this method is superior to previous attempts that looked into localization in crowded outdoor environments." @default.
- W2849573857 created "2018-07-19" @default.
- W2849573857 creator A5071827522 @default.
- W2849573857 date "2018-05-01" @default.
- W2849573857 modified "2023-09-26" @default.
- W2849573857 title "Partitioned environments for visual localization" @default.
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- W2849573857 doi "https://doi.org/10.1109/siu.2018.8404239" @default.
- W2849573857 hasPublicationYear "2018" @default.
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