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Height and Texture Modeling of Road Surfaces for Camera-Based HDMap Construction
http://doi.org/10.5626/JOK.2024.51.9.835
With increasing demand for construction and updating of HD maps for autonomous vehicles, multi-camera systems are being used as cost-effective sensors for Mobile Mapping System (MMS). Stereo matching among multi-view images, image feature point matching, and visual localization are utilized for such camera-based 3D map reconstruction. In this paper, we proposed a methodology for estimating height of road surfaces and texture registration utilizing hexgrid model, keyframe poses and 3D point clouds based on multi-view images. The proposed methodology could reconstruct high-density and high-accuracy 3D point cloud of road surfaces base on a multi-camera system mounted on the upper part of a vehicle. Our experimental results showed that the proposed method created a precise road model with a minimum point spacing of 0.025 m on a MMS equipped with ultra-wide angle fisheye cameras and GPS.
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