SYSTEM AND METHOD OF DETECTING OBJECTS IN SCENE POINT CLOUD
First Claim
1. A method of detecting one or more objects in a three-dimensional point cloud scene, the method being implemented by a computer system that includes one or more processors configured to execute computer modules, the method comprising:
- receiving, by one or more processors, a three-dimensional point cloud scene, the three-dimensional point cloud scene comprising a plurality of points;
classifying, by the one or more processors, at least a portion of the plurality of points in the three-dimensional point cloud into two or more categories by applying a classifying-oriented three-dimensional local descriptor and learning-based classifier;
extracting, by the one or more processors, from the three-dimensional point cloud scene one or more clusters of points utilizing the two or more categories by applying at least one of segmenting and clustering; and
matching, by the one or more processors, the extracted clusters with objects within a library by applying a matching-oriented three-dimensional local descriptor.
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Abstract
A system and method of detecting one or more objects in a three-dimensional point cloud scene are provided. The method includes receiving a three-dimensional point cloud scene, the three-dimensional point cloud scene comprising a plurality of points; classifying at least a portion of the plurality of points in the three-dimensional point cloud into two or more categories by applying a classifying-oriented three-dimensional local descriptor and learning-based classifier; extracting from the three-dimensional point cloud scene one or more clusters of points utilizing the two or more categories by applying at least one of segmenting and clustering; and matching the extracted clusters with objects within a library by applying a matching-oriented three-dimensional local descriptor.
82 Citations
20 Claims
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1. A method of detecting one or more objects in a three-dimensional point cloud scene, the method being implemented by a computer system that includes one or more processors configured to execute computer modules, the method comprising:
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receiving, by one or more processors, a three-dimensional point cloud scene, the three-dimensional point cloud scene comprising a plurality of points; classifying, by the one or more processors, at least a portion of the plurality of points in the three-dimensional point cloud into two or more categories by applying a classifying-oriented three-dimensional local descriptor and learning-based classifier; extracting, by the one or more processors, from the three-dimensional point cloud scene one or more clusters of points utilizing the two or more categories by applying at least one of segmenting and clustering; and matching, by the one or more processors, the extracted clusters with objects within a library by applying a matching-oriented three-dimensional local descriptor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A system of detecting one or more objects in a three-dimensional point cloud scene, the system comprising a processor configured to:
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receive a three-dimensional point cloud scene, the three-dimensional point cloud scene comprising a plurality of points; classify at least a portion of the plurality of points in the three-dimensional point cloud into two or more categories by applying a classifying-oriented three-dimensional local descriptor and learning-based classifier; extract from the three-dimensional point cloud scene one or more clusters of points utilizing the two or more categories by applying at least one of segmenting and clustering; and match the extracted clusters with objects within a library by applying a matching-oriented three-dimensional local descriptor.
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- 18. The system according to claim 18, wherein the processor is configured to filter each of the extracted clusters to obtain filtered clusters with desired characteristics and then match the filtered clusters with the objects within the library by applying the matching-oriented three-dimensional local descriptor.
Specification