Rapid point cloud alignment and classification with basis set learning
地域：
WA
WA Seattle
摘要
A system configured to process an input point cloud, which represents an object using unstructured data points, to generate a feature vector that has an ordered structure and a fixed length. The system may process the input point cloud using a basis point set to generate the feature vector. For example, for each basis point in the basis point set, the system may identify a closest data point in the point cloud data and store a distance value or other information associated with the closest data point in the feature vector. The system may process the feature vector using a trained model to generate output data, such as performing point cloud registration to generate mesh data, point cloud classification to generate classification data, and/or the like.
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The system 100 may obtain (132) a basis point set with which to process the point cloud 114. For example, the system 100 may generate the basis point set or retrieve a preconfigured basis point set. The basis point set may be a fixed set of k random points that may be selected from a random uniform ball, as shown below.
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