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
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;
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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20 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 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; 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, 10)
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11. 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 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; 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 (12, 13, 14, 15)
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16. A program product comprising program instructions embodied on a 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 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; 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 (17, 18, 19, 20)
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Specification