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Conference papers

Geometric-visual descriptor for improved image based localization

Abstract : This paper addresses the problem of image based localization. The goal is to find quickly and accurately the relative pose from a query taken from a stereo camera and a map obtained using visual SLAM which contains poses and 3D points associated to descriptors. In this paper we introduce a new method that leverages the stereo vision by adding geometric information to visual descriptors. This method can be used when the vertical direction of the camera is known (for example on a wheeled robot). This new geometric visual descriptor can be used with several image based localization algorithms based on visual words. We test the approach with different datasets (indoor, outdoor) and we show experimentally that the new geometric-visual descriptor improves standard image based localization approaches.
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Contributor : Eric Royer Connect in order to contact the contributor
Submitted on : Thursday, November 26, 2020 - 9:41:32 AM
Last modification on : Wednesday, November 3, 2021 - 8:12:52 AM
Long-term archiving on: : Saturday, February 27, 2021 - 6:24:58 PM


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Distributed under a Creative Commons Attribution 4.0 International License


  • HAL Id : hal-03024935, version 1


Achref Ouni, Eric Royer, Marc Chevaldonné, Michel Dhome. Geometric-visual descriptor for improved image based localization. VCIP, Dec 2020, MACAO, China. ⟨hal-03024935⟩



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