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Strip histogram grid for efficient segmentation of 3D point clouds from urban environments

  • US 8,620,089 B1
  • Filed: 12/22/2009
  • Issued: 12/31/2013
  • Est. Priority Date: 12/22/2009
  • Status: Expired due to Fees
First Claim
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1. A method of recognizing features from sensed data points collected in a 3D environment comprising:

  • sensing the 3D environment using a sensor that collects a plurality of sensed data points from the 3D environment, each sensed data point having spatial coordinate information in three dimensions x, y and z;

    populating a strip histogram grid having a plurality of strips, each strip having a z, a dx dimension and a dy dimension, wherein dx is a portion of an x dimension of the strip histogram grid and dy is a portion of a y dimension of the strip histogram grid, and wherein the z dimension is divided into a plurality of dz portions of the z dimension, so that each strip is divided into a plurality of cells, each cell having a dimension of dx, dy, and dz, by assigning each sensed data point to a strip in the strip histogram grid that has x, y and z dimensions that encompass the spatial coordinate information of the respective assigned sensed data point, and assigning each sensed data point to one of the plurality of dz portions of the z dimension,initializing a ground support variable for each cell of the plurality of cells to zero;

    incrementing the ground support variable associated with a respective cell by 1 each time a sensed data point is assigned to that respective cell or a sensed data point is assigned to a cell in a surrounding strip having a same z dimension as the respective cell and being within a set distance of the respective cell; and

    estimating the local ground plane for the respective strip as being the lowest z level corresponding to a cell within the respective strip with a respective ground support variable greater than a threshold.

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