Proceedings of the 27th ACM International Conference on Multimedia 2019
DOI: 10.1145/3343031.3350924
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Monocular Visual Object 3D Localization in Road Scenes

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Cited by 22 publications
(25 citation statements)
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“…This formulation assumes coplanarity of the ego car and the object being 3D backprojected. We adaptively choose relatively reliable features from sparse or dense features generated over a depthmap [14] according to [1] to fit the ground plane using RANSAC.…”
Section: Ground Plane Estimationmentioning
confidence: 99%
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“…This formulation assumes coplanarity of the ego car and the object being 3D backprojected. We adaptively choose relatively reliable features from sparse or dense features generated over a depthmap [14] according to [1] to fit the ground plane using RANSAC.…”
Section: Ground Plane Estimationmentioning
confidence: 99%
“…Giving an accurate 3D localization of other traffic participants [1,2,3,4] is extremely essential for safety issue in the field of autonomous driving. Currently, most platforms are equipped with LiDAR, Radar, and cameras.…”
Section: Introductionmentioning
confidence: 99%
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