System and method for extraction of features from a 3-D point cloud
First Claim
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1. A method of extracting a feature from a point cloud, the method comprising:
- receiving a three-dimensional (3-D) point cloud representing objects in a scene, the 3-D point cloud containing a plurality of data points;
generating a plurality of hypothetical features based on data points in the 3-D point cloud, wherein the data points corresponding to each hypothetical feature are inlier data points for the respective hypothetical feature and the respective hypothetical feature has the appearance of a geometric two-dimensional manifold, wherein the plurality of hypothetical features are planar features and the geometrical parameters for each respective planar feature comprise a normal vector and an orthogonal distance from the respective planar feature to an origin; and
selecting a hypothetical feature, which provides a value of a quality function that is closer to a desired value than the value of the quality function provided by the other hypothetical features, as representative of an object in the scene;
calculating new inlier data points based on the geometrical parameters of a fraction of the inlier data points;
wherein generating each of the plurality of hypothetical features comprises;
selecting at least three data points;
calculating geometrical parameters for the respective hypothetical feature based on the at least three data points; and
using the calculated geometrical parameters to determine the point-to-feature distance for each data point, wherein each data point whose respective point-to-feature distance is less than or equal to a first threshold value is identified as an inlier data point.
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Abstract
A method of extracting a feature from a point cloud comprises receiving a three-dimensional (3-D) point cloud representing objects in a scene, the 3-D point cloud containing a plurality of data points; generating a plurality of hypothetical features based on data points in the 3-D point cloud, wherein the data points corresponding to each hypothetical feature are inlier data points for the respective hypothetical feature; and selecting the hypothetical feature having the most inlier data points as representative of an object in the scene.
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Citations
17 Claims
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1. A method of extracting a feature from a point cloud, the method comprising:
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receiving a three-dimensional (3-D) point cloud representing objects in a scene, the 3-D point cloud containing a plurality of data points; generating a plurality of hypothetical features based on data points in the 3-D point cloud, wherein the data points corresponding to each hypothetical feature are inlier data points for the respective hypothetical feature and the respective hypothetical feature has the appearance of a geometric two-dimensional manifold, wherein the plurality of hypothetical features are planar features and the geometrical parameters for each respective planar feature comprise a normal vector and an orthogonal distance from the respective planar feature to an origin; and selecting a hypothetical feature, which provides a value of a quality function that is closer to a desired value than the value of the quality function provided by the other hypothetical features, as representative of an object in the scene; calculating new inlier data points based on the geometrical parameters of a fraction of the inlier data points; wherein generating each of the plurality of hypothetical features comprises; selecting at least three data points; calculating geometrical parameters for the respective hypothetical feature based on the at least three data points; and using the calculated geometrical parameters to determine the point-to-feature distance for each data point, wherein each data point whose respective point-to-feature distance is less than or equal to a first threshold value is identified as an inlier data point. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system comprising:
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a sensor operable to obtain a set of three-dimensional (3-D) data points for a scene; a processing unit coupled to the sensor and operable to; generate a plurality of hypothetical features based on the plurality of data points, each hypothetical feature having a plurality of inlier data points and the appearance of a geometric two-dimensional manifold, wherein the plurality of hypothetical features are planar features and the geometrical parameters for each respective planar feature comprise a normal vector and an orthogonal distance from the respective planar feature to an origin; select the hypothetical feature that provides a value of a quality function that is closer to a desired value than the value of the quality function provided by the other hypothetical features; and calculate new inlier data points based on the geometrical parameters of a fraction of the plurality of inlier data points; wherein the processing unit is further operable to generate each of the plurality of hypothetical features by; selecting at least three data points; calculating geometrical parameters for the respective hypothetical feature based on the at least three data points; and calculating a point-to-feature distance for each data point based on the calculated geometrical parameters, wherein each data point whose respective point-to-feature distance is less than or equal to a first threshold value is identified as an inlier data point. - View Dependent Claims (11, 12, 13)
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14. A program product comprising program instructions embodied on a non-transitory processor-readable medium for execution by a programmable processor, wherein the program instructions are operable to cause the programmable processor to:
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generate a plurality of hypothetical features based on a plurality of data points in a three-dimensional (3-D) point cloud received from a sensor, each hypothetical feature having a plurality of inlier data points and the appearance of a geometric two-dimensional manifold, wherein the plurality of hypothetical features are planar features and the geometrical parameters for each respective planar feature comprise a normal vector and an orthogonal distance from the respective planar feature to an origin; select the hypothetical feature that provides a value of a quality function that is closer to a desired value than the value of the quality function provided by the other hypothetical planes as representative of an object feature in a scene; and calculate new inlier data points based on the geometrical parameters of a fraction of the inlier data points; wherein the program instructions are operable to cause the programmable processor to generate each of the plurality of hypothetical features by causing the programmable processor to; select at least three data points; calculate geometrical parameters for the respective hypothetical feature based on the at least three data points; and calculate a point-to-feature distance for each data point based on the calculated geometrical parameters, wherein each data point whose respective point-to-feature distance is less than or equal to a first threshold value is identified as an inlier data point. - View Dependent Claims (15, 16, 17)
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Specification