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Recognition and pose determination of 3D objects in 3D scenes

  • US 8,830,229 B2
  • Filed: 01/06/2011
  • Issued: 09/09/2014
  • Est. Priority Date: 05/07/2010
  • Status: Active Grant
First Claim
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1. A method for recognizing instances of a 3D object represented by 3D object data in a 3D scene represented by 3D scene data and for determining the 3D poses of said instances comprising the following steps:

  • (a) providing 3D scene data and 3D object data;

    (b) selecting at least one reference point from the 3D scene data;

    (c) computing, for each selected reference point, pose candidates for the 3D object under the assumption that said reference point is part of the 3D object, by;

    (c1) representing a space of possible pose candidates by two parameters, where a first parameter is a 2D point on the surface of the 3D object data that corresponds to said reference scene point, and a second parameter is a rotation angle;

    (c1a) representing the first parameter as index into a set of points selected from the 3D object data and sampling the second parameter;

    (c2) creating a counter for each pose space sample of step (c1a);

    (c3) selecting a set of scene points from the 3D scene data;

    (c4) computing, for each selected scene point, matching poses such that both the selected scene point and the reference point are on the surface of the 3D object by (c4a) computing a point pair descriptor that describes the reference scene point and the current scene point and their geometric relation;

    (c4b) searching for point pairs in the 3D object data similar to said scene point pair using said point pair descriptor;

    (c4c) computing, for each such similar point pair, the point corresponding to the reference scene point, and the rotation angle that aligns the scene point pair and the object point pair, after aligning the reference scene point, its corresponding object point and their surface normals;

    (c5) increasing, for each corresponding point and rotation angle computed in step (c4c), the counter for the corresponding pose space sample; and

    (c6) detecting peak counter values in the sampled pose space and selecting the corresponding pose samples as pose candidates.

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