11. The method as set forth in claim 9 , wherein the 3D point cloud is down sampled using a 3D voxel grid having a plurality of voxels, where the 3D voxel grid is positioned over the 3D point cloud such that all the data points in each voxel are down-sampled to a centroid for each voxel.
9. A method for filtering, segmenting and recognizing objects, the method comprising an act of: causing one or more processors to execute instructions encoded on a non-transitory computer-readable medium, such that upon execution, 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.