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- W3081856871 abstract "Real-time camera pose estimation is one of the indispensable technologies for Augmented Reality (AR). While a large body of work in Visual Odometry (VO) has been proposed for AR, practical challenges such as scale ambiguities and accumulative errors still remain especially when we apply VO to large-scale scenes due to limited hardware and resources. We propose a camera pose registration method, where a local VO is consecutively optimized with respect to a large-scale scene map on the fly. This framework enables the scale estimation between a VO map and a scene map and reduces accumulative errors by finding corresponding locations in the map to the current frame and by on-the-fly pose graph optimization. The results using public datasets demonstrated that our approach reduces the accumulative errors of naive VO." @default.
- W3081856871 created "2020-09-08" @default.
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- W3081856871 date "2020-01-01" @default.
- W3081856871 modified "2023-10-16" @default.
- W3081856871 title "Global-Map-Registered Local Visual Odometry Using On-the-Fly Pose Graph Updates" @default.
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- W3081856871 doi "https://doi.org/10.1007/978-3-030-58465-8_23" @default.
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