Apparatus and method for point cloud assembly
View Patent ↗A method and apparatus for point cloud assembly are described. In one embodiment, the method includes the obtaining of a data set of a first point cloud and a data set of a second point cloud. Once obtained, a portion of geometry defined by each respective data set is identified, which substantially describes a similar geometric shape. Next, a transformation is computed, such that the portion of geometry in each data set aligns to substantially minimize alignment error. Finally, the computed transformation is applied to the first point cloud to register the first point cloud relative to the second point cloud. In one embodiment, identification of the geometric portion describing a substantially similar geometric shape may be performed utilizing geometric reference point information, image texture information or a combination thereof.
1. A method comprising:
obtaining a data set of a first point cloud and a data set of a second point cloud;
identifying a portion of geometry defined by each respective data set which describes a substantially similar geometric shape;
computing a transformation such that the portion of geometry in each data set align to substantially minimize alignment error; and
applying the transformation to the first point cloud to register it relative to the second point cloud.
2. The method of claim 1 wherein computing comprises:
generating values for a relative rotation of a portion of the identified geometry within the first and second point clouds respectively.
3. The method of claim 2 wherein computing comprises:
constructing a rotation matrix for the portion of geometry defined by each respective data set which describes the substantially similar geometric shape.
4. The method of claim 1 wherein computing comprises:
identifying a relative scale factor between a portion of the identified geometry within the first and second point clouds respectively.
5. The method of claim 1 wherein computing comprises:
generating values for a relative translation of a portion of the identified geometry within the first and second point cloud respectively.
6. The method of claim 1 wherein computing the transformation comprises:
calculating a geometric mean of a spatial distribution of the identified portion of geometry of at least one point cloud.
7. The method of claim 1 wherein computing the transformation comprises:
calculating a centroid of a spatial distribution of the identified portion of geometry of at least one point cloud.
8. The method of claim 1 wherein computing the transformation comprises:
combining calculations for a relative rotation, scale and translation of the identified portion of geometry of first and second point clouds respectively.
9. The method of claim 1 wherein the first and the second point clouds represent portions of a single physical object.
10. The method of claim 1 wherein identifying occurs substantially automatically.
11. A method comprising:
obtaining a data set of a first point cloud and a data set of a second point cloud;
obtaining an image containing texture for a portion of geometry in each respective data set;
identifying a first portion of the texture and a second portion of the texture associated with each respective data set that represents substantially a same surface;
computing a relative texture transformation of the first and second data sets such that the portions of texture associated with each data set align to substantially minimize texture alignment error;
identifying a portion of geometry defined by each respective data set which describes a substantially similar geometric shape;
computing a relative geometric transformation such that the portion of geometry in each respective data set align to substantially minimize alignment error;
adjusting the texture transformation based on the geometric transformation; and
applying the adjusted texture transformation to the first texture to register it relative to the second texture.
12. A computer readable storage medium including program instructions that direct a computer to perform one or more operations when executed by a processor, the one or more operations comprising:
obtaining a data set of a first point cloud and a data set of a second point cloud;
identifying a portion of geometry defined by each respective data set which describes a substantially similar geometric shape;
computing a transformation such that the portion of geometry in each data set align to substantially minimize alignment error; and
applying the transformation to the first point cloud to register it relative to the second.