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Assessing the Reliability and the Accuracy of Attitude Extracted from Visual Odometry for LIDAR Data Georeferencing

Abstract : Airborne LiDAR systems require the use of Direct Georeferencing (DG) in order to compute the coordinates of the surveyed point in the mapping frame. An UAV platform does not derogate to this need, but its payload has to be lighter than this installed onboard so the manufacturer needs to find an alternative to heavy sensors and navigation systems. For the georeferencing of these data, a possible solution could be to replace the Inertial Measurement Unit (IMU) by a camera and record the optical flow. The different frames would then be processed thanks to photogrammetry so as to extract the External Orientation Parameters (EOP) and, therefore, the path of the camera. The major advantages of this method called Visual Odometry (VO) is low cost, no drifts IMU-induced, option for the use of Ground Control Points (GCPs) such as on airborne photogrammetry surveys. In this paper we shall present a test bench designed to assess the reliability and accuracy of the attitude estimated from VO outputs. The test bench consists of a trolley which embeds a GNSS receiver, an IMU sensor and a camera. The LiDAR is replaced by a tacheometer in order to survey the control points already known. We have also developped a methodology applied to this test bench for the calibration of the external parameters and the computation of the surveyed point coordinates. Several tests have revealed a difference about 2-3 centimeters between the control point coordinates measured and those already known.
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Contributor : Jérôme Verdun Connect in order to contact the contributor
Submitted on : Sunday, March 28, 2021 - 7:31:07 PM
Last modification on : Monday, February 21, 2022 - 3:38:18 PM
Long-term archiving on: : Tuesday, June 29, 2021 - 6:11:44 PM


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Boris Leroux, José Cali, Jérôme Verdun, Laurent Morel, H. He. Assessing the Reliability and the Accuracy of Attitude Extracted from Visual Odometry for LIDAR Data Georeferencing. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, XLII-2/W6, pp.201-208. ⟨10.5194/isprs-archives-XLII-2-W6-201-2017⟩. ⟨hal-03183736⟩



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