Methods and apparatus for testing multiple fields for machine vision

Patent metadata

Field	Value
Publication number	US-10878299-B2
Application number	US-201816129170-A
Country	US
Kind code	B2
Filing date	Sep 12, 2018
Priority date	Sep 12, 2018
Publication date	Dec 29, 2020
Grant date	Dec 29, 2020

Abstract

The techniques described herein relate to methods, apparatus, and computer readable media configured to test a pose of a three-dimensional model. A three-dimensional model is stored, the three dimensional model comprising a set of probes. Three-dimensional data of an object is received, the three-dimensional data comprising a set of data entries. The three-dimensional data is converted into a set of fields, comprising generating a first field comprising a first set of values, where each value of the first set of values is indicative of a first characteristic of an associated one or more data entries from the set of data entries, and generating a second field comprising a second set of values, where each second value of the second set of values is indicative of a second characteristic of an associated one or more data entries from the set of data entries, wherein the second characteristic is different than the first characteristic. A pose of the three-dimensional model is tested with the set of fields, comprising testing the set of probes to the set of fields, to determine a score for the pose.

First claim

The invention claimed is:

1. A computerized method for testing a pose of a three-dimensional model to three-dimensional data, the method comprising:
storing a three-dimensional model, the three-dimensional model comprising a set of probes, each probe including data for an associated portion of the three-dimensional model;
receiving three-dimensional data of an object, the three-dimensional data comprising a set of data entries;
converting the three-dimensional data into a set of fields, comprising:
generating a first field comprising a first set of values, wherein each value of the first set of values is indicative of a first characteristic of an associated one or more data entries from the set of data entries; and
generating a second field comprising a second set of values, wherein each value of the second set of values is indicative of a second characteristic of an associated one or more data entries from the set of data entries, wherein the second characteristic is different than the first characteristic; and

testing a pose of the three-dimensional model with the set of fields, comprising testing the set of probes to the set of fields, to determine a score for the pose, wherein testing the set of probes to the set of fields comprises:
determining a first score for the set of probes being tested against the first set of values of the first field;
determining a second score for the set of probes being tested against the second set of values of the second field; and
determining the score for the pose based on the first score and the second score.

2. The method of claim 1 , wherein generating the first field and/or the second field comprises generating a three-dimensional array for each field, wherein:
each three-dimensional array comprises a set of three indexes, comprising an index for each dimension; and
each three-dimensional array implies x, y, and z locations of each associated value of the first set of values and/or the second set of values by the set of three indexes.

3. The method of claim 1 , wherein the set of probes, the first set of values of the first field, and the second set of values of the second field comprise surface normal data, edge boundary data, and/or intensity data.

4. The method of claim 1 , wherein testing the pose to determine the score for the pose comprises summing a dot product for each probe of the set of probes and associated value of the first set of values and/or the second set of values.

5. The method of claim 1 , further comprising:
testing a plurality of poses to determine a plurality of associated scores;
determining one or more poses of the plurality of poses comprising a score above a predetermined threshold to generate a set of poses; and
storing, for subsequent processing, the set of poses.

6. The method of claim 5 , wherein each pose in the set of poses represents a local peak of the plurality of associated scores, the method further comprising refining the set of poses to determine a top pose of the three-dimensional model.

7. A system for testing a pose of a three-dimensional model to three-dimensional data, the system comprising one or more processors configured to:
store a three-dimensional model, the three-dimensional model comprising a set of probes, each probe including data for an associated portion of the three-dimensional model;
receive three-dimensional data of an object, the three-dimensional data comprising a set of data entries;
convert the three-dimensional data into a set of fields, comprising:
generating a first field comprising a first set of values, wherein each value of the first set of values is indicative of a first characteristic of an associated one or more data entries from the set of data entries; and
generating a second field comprising a second set of values, wherein each value of the second set of values is indicative of a second characteristic of an associated one or more data entries from the set of data entries, wherein the second characteristic is different than the first characteristic; and

test a pose of the three-dimensional model with the set of fields, comprising testing the set of probes to the set of fields, to determine a score for the pose, wherein testing the set of probes to the set of fields comprises:
determining a first score for the set of probes being tested against the first set of values of the first field;
determining a second score for the set of probes being tested against the second set of values of the second field; and
determining the score for the pose based on the first score and the second score.

8. The system of claim 7 , wherein generating the first field and/or the second field comprises generating a three-dimensional array for each field, wherein:
each three-dimensional array comprises a set of three indexes, comprising an index for each dimension; and
each three-dimensional array implies x, y, and z locations of each associated value of the first set of values and/or the second set of values by the set of three indexes.

9. The system of claim 7 , wherein the set of probes, the first set of values of the first field, and the second set of values of the second field comprise surface normal data, edge boundary data, and/or intensity data.

10. The system of claim 7 , wherein testing the pose to determine the score for the pose comprises summing a dot product for each probe of the set of probes and associated value of the first set of values and/or the second set of values.

11. The system of claim 7 , wherein the one or more processors are further configured to:
test a plurality of poses to determine a plurality of associated scores;
determine one or more poses of the plurality of poses comprising a score above a predetermined threshold to generate a set of poses; and
store, for subsequent processing, the set of poses.

12. The system of claim 11 , wherein each pose in the set of poses represents a local peak of the plurality of associated scores, the one or more processors further configured to refine the set of poses to determine a top pose of the three-dimensional model.

13. At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform the acts of:
storing a three-dimensional model, the three-dimensional model comprising a set of probes each probe including data for an associated portion of the three-dimensional model;
receiving three-dimensional data of an object, the three-dimensional data comprising a set of data entries;
converting the three-dimensional data into a set of fields, comprising:
generating a first field comprising a first set of values, wherein each value of the first set of values is indicative of a first characteristic of an associated one or more data entries from the set of data entries; and
generating a second field comprising a second set of values, wherein each value of the second set of values is indicative of a second characteristic of an associated one or more data entries from the set of data entries, wherein the second characteristic is different than the first characteristic; and

testing a pose of the three-dimensional model with the set of fields, comprising testing the set of probes to the set of fields, to determine a score for the pose, wherein testing the set of probes to the set of fields comprises:
determining a first score for the set of probes being tested against the first set of values of the first field;
determining a second score for the set of probes being tested against the second set of values of

Assignees

• Cognex Corp

Inventors

• Hoelscher Andrew
• Bogan Nathaniel

Classifications

• G06V20/653

  by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces · CPC title

• G06V30/2504 Primary

  Coarse or fine approaches, e.g. resolution of ambiguities or multiscale approaches · CPC title

• G06T7/75 Primary

  involving models · CPC title

• G06T2207/10028

  Range image; Depth image; 3D point clouds · CPC title

• G06K9/00214

  Physics · mapped topic