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- W2912682393 abstract "Aiming at the problem of loop closure detection in simultaneous localization and mapping for mobile robots, we propose a method based on ORB features and BOW model. We extract binary features from the required pictures, then modify a traditional k-means structure according to the characteristics of binary words, obtain the visual dictionary online. The similarity of images can be computed based on the visual words. A Bayesian filter was introduced to select final loop images to guarantee the success rate of the closed-loop detection. Finally, an Epipolar Constraint is performed to remove the wrong images. The proposed approach is detected in several datasets, and the effectiveness of the method is demonstrated by the comparison with several classical algorithms." @default.
- W2912682393 created "2019-02-21" @default.
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- W2912682393 date "2018-07-01" @default.
- W2912682393 modified "2023-10-16" @default.
- W2912682393 title "A Loop Closure Detection Method Using Binary Feature Descriptors" @default.
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- W2912682393 doi "https://doi.org/10.1109/wcica.2018.8630537" @default.
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