Patent Document ID: 9633483
Application ID: 14669833

Base Claim:
1. A system for filtering, segmenting and recognizing objects, comprising: one or more processors and a memory, the memory having executable instructions encoded thereon, such that upon execution of the instructions, the one or more processors perform operations of: down sampling a three-dimensional (3D) point cloud having a plurality of data points in 3D space to generate a down-sampled 3D point cloud P with reduced data points in the 3D space; identifying and removing a ground plane in the down-sampled 3D point cloud to leave non-ground data points in the down-sampled 3D point cloud; generating a set of 3D candidate blobs by clustering the non-ground data points to generate a plurality of 3D blobs, each of the 3D blobs having a cluster size; extracting features from each 3D candidate blob, the features being vectors that represent morphological characteristics of each 3D candidate blob; and classifying at least one of the 3D candidate blobs as a pre-defined object class based on the extracted features by assigning a semantic meaning to a segmented real-world individual object.

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Claim 6:
6. The system as set forth in claim 1 , wherein clustering the non-ground data points to generate a plurality of 3D blobs further comprises operations of: creating a kd-tree representation for the down-sampled 3D point cloud P; generating an empty list of clusters C, and a queue of the points that need to be checked Q, for every point p i εP, performing the following operations: adding p i to the current queue Q; for every point p i εQ do: recursively adding all neighboring points in a sphere with a fixed radius, and when the list of all points in Q has been processed, add Q to the list of clusters C, and reset Q to an empty list; and terminating when all points in the original point cloud have been processed and are now part of the list of clusters C.