Automatic Classification of Eardrum Shape
US-2018260616-A1 · Sep 13, 2018 · US
US11216951B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11216951-B2 |
| Application number | US-201916693161-A |
| Country | US |
| Kind code | B2 |
| Filing date | Nov 22, 2019 |
| Priority date | May 25, 2017 |
| Publication date | Jan 4, 2022 |
| Grant date | Jan 4, 2022 |
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A computer-implemented method for representing environmental elements includes receiving scan data comprising at least a point cloud representing at least an environmental element from a sensor, segmenting the point cloud into point clusters, and partitioning the point clusters into hierarchical grids. The method also includes establishing a Gaussian distribution for points in each cell of each of the hierarchical grids, and constructing a Gaussian Mixture Model based on the Gaussian distribution for representing the environmental element.
Opening claim text (preview).
What is claimed is: 1. A computer-implemented method for representing environmental elements, comprising: receiving scan data comprising at least a point cloud representing at least an environmental element from a sensor; segmenting the point cloud into point clusters using a region growing algorithm with a predetermined criterion of smooth; partitioning the point clusters into hierarchical grids; establishing a Gaussian distribution for points in each cell of each of the hierarchical grids; and constructing a Gaussian Mixture Model based on the Gaussian distribution for representing the environmental element, wherein the predetermined criterion of smooth is derived by: for each point of the point cloud, getting its neighboring points; transforming the neighboring points into a local operation plane; for each point of the point cloud, calculating principal curvatures of the local surface; calculating surface curvature at one point of the point cloud to the direction of another point of the point cloud, surface curvature at the another point to the direction of the one point, and torsion of surface from the one point to the direction of the another point; and establishing the predetermined criterion of smooth as the absolute value of the surface curvature at the one point to the direction of the another point being smaller than a threshold, the absolute value of the surface curvature at the another point to the direction of the one point being smaller than a threshold, and the absolute value of the torsion of surface from the one point to the direction of the another point being smaller than a threshold, and wherein the surface curvature K ij at the one point to the direction of the another point G p j is denoted as: K ij = d ij T d ij ( v i 1 v i 2 ) H i ( v i 1 v i 2 ) T d ij d ij , the surface curvature K ji at the another point G p j to the direction of the one point G p i is denoted as K ji = d ij T d ij ( v j 1 v j 2 ) H j ( v j 1 v
involving region growing; involving region merging; involving connected component labelling · CPC title
Three-dimensional [3D] objects · CPC title
Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads · CPC title
Graphical representations · CPC title
Terrestrial scenes (scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59) · CPC title
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