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US 11,380,003 B2Granted
Monocular camera localization in large scale indoor sparse LiDAR point cloud
AssigneeBlack Sesame Technologies Inc.
InventorsYu Chen, Guan Wang
Life of this patent
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Abstract
A method of camera localization, comprising, receiving a camera image, receiving a LiDAR point cloud, estimating an initial camera pose for the camera image, sampling an initial set of depth projections within the LiDAR point cloud, measuring a similarity of the initial camera pose to the initial set of depth projections and deriving a subsequent set of depth projections based on the measured similarity.
Claims16
A method of camera localization, comprising:
- receiving a camera image;
- receiving a LiDAR point cloud;
- estimating an initial camera pose for the camera image;
- sampling an initial set of depth projections within the LiDAR point cloud;
- measuring a similarity of the initial camera pose to the initial set of depth projections;
- and
- deriving a subsequent set of depth projections based on the measured similarity in a camera image feature space.
4 more elements
A method of camera localization, comprising:
- receiving a camera image;
- receiving a LiDAR point cloud;
- estimating an initial camera pose for the camera image;
- sampling an initial set of depth projections within the LiDAR point cloud;
- measuring a similarity of the initial camera pose to the initial set of depth projections as a state value;
- measuring a regression of the similarity of the initial camera pose to the initial set of depth projections;
- measuring a gradient of the similarity of the initial camera pose to the initial set of depth projections;
- and
- deriving a subsequent set of depth projections based on the gradient of the similarity in a camera image feature space.
6 more elements
Dependencies are inferred from the claim text.