US 7,336,814 B2 · Method and apparatus for machine-vision

Abstract

A system and method facilitate machine-vision, for example three-dimensional pose estimation for target objects, using one or more images sensors to acquire images of the target object at one or more positions, and to identify features of the target object in the resulting images. A set of equations is set up exploiting invariant physical relationships between features such as constancy of distances, angles, and areas or volumes enclosed by or between features. The set of equations may be solved to estimate a 3D pose. The number of positions may be determined based on the number of image sensors, number of features identified, and/or number of known physical relationships between less than all features. Knowledge of physical relationships between image sensors and/or between features and image sensors may be employed. A robot path may be transformed based on the pose, to align the path with the target object.

Claims39

Dependent claims

A method useful in machine-vision of objects, the method comprising:

acquiring a number of images of a first view of a training object from a number of image sensors;
identifying a number of features of the training object in the acquired at least one image of the first view;
determining a number of additional views to be obtained based at least in part on the number of image sensors, the number of features identified, the number of features having an invariant physical relationship associated thereto, and a type of the invariant physical relationship associated with the features, sufficient to provide a system of equations and unknowns where the number of unknowns is not greater than the number of equations;
acquiring at least one image of each of the number of additional views of the training object by the at least one camera;
and
identifying at least some of the number of features of the training object in the acquired at least one image of the number of additional views of the training object
employing at least one of a consistency of physical relationships between some of the identified features to set up the system of equations;
and
automatically computationally solving the system of equations.

6 more elements

A machine-vision system, comprising:

at least one image sensor operable to acquire images of a training object and of target objects;
processor-readable medium storing instructions for facilitating machine-vision for objects having invariant physical relationships between a number of features on the objects, by:
acquiring a number of images of a first view of a training object from a number of image sensors;
identifying a number of features of the training object in the acquired at least one image of the first view;
determining a number of additional views to be obtained based at least in part on the number of image sensors, the number of features identified, the number of features having an invariant physical relationship associated thereto, and a type of the invariant physical relationship associated with the features, sufficient to provide a system of equations and unknowns where the number of unknowns is not greater than the number of equations;
employing at least one of a consistency of physical relationships between some of the identified features to set up the system of equations;
and
automatically computationally solving the system of equations;
and
a processor coupled to receive acquired images from the at least one image sensor and operable to execute the instructions stored in the processor-readable medium.

7 more elements

A processor readable medium storing instructions for causing a processor to facilitate machine-vision for objects having invariant physical relationships between a number of features on the objects, by:

acquiring a number of images of a first view of a training object from a number of cameras;
identifying a number of features of the training object in the acquired at least one image of the first view;
determining a number of additional views to be obtained based at least in part on the number of image sensors, the number of features identified, the number of features having an invariant physical relationship associated thereto, and a type of the invariant physical relationship associated with the features, sufficient to provide a system of equations and unknowns where the number of unknowns is not greater than the number of equations;
employing at least one of a consistency of physical relationships between some of the identified features to set up the system of equations;
and
automatically computationally solving the system of equations.

3 more elements

A method useful in machine-vision of objects, the method comprising:

acquiring a number of images of a first view of a training object from a number of cameras;
identifying a number of features of the training object in the acquired at least one image of the first view;
associating parameters to less than all of the identified features which parameters define an invariant physical relationship between either the feature and at least one other feature, the feature and the at least one camera, or between the at least one camera and at least another camera where an invariant physical relationship between each one of the features and at least one other feature is not known when associating the parameters before a runtime;
determining a number of additional views to be obtained based at least in part on the number of cameras, the number of features identified, and the number of features having parameters associated thereto, sufficient to provide a system of equations and unknowns where the number of unknowns is not greater than the number of equations;
and
acquiring at least one image of each of the number of additional views of the training object by the at least one camera;
identifying at least some of the number of features of the training object in the acquired at least one image of the number of additional views of the training object.

4 more elements

A method useful in machine-vision for objects having invariant physical relationships between a number of features on the objects, the method comprising:

in a pre-runtime environment:
acquiring at least one image of a first view of a training object by at least one image sensor;
identifying a number of features of the training object in the acquired at least one image of the first view;
and
associating a number of parameters to less than all of the identified features which define an invariant physical relationship between the either the feature and at least one other feature or between the feature and the at least one image sensor;
determining a number of additional views to be obtained based at least in part on the number of image sensors acquiring at least one image, the number of features of the training object identified, the number of features having parameters associated therewith, and a type of invariant physical relationship associated with each of the parameter;
acquiring at least one image of a second view of the training object by the at least one image sensor;
and
identifying at least some of the number of features of the training object in the acquired at least one image of the second view;
and
in at least one of a pre-run time environment or a runtime environment, computationally determining a local model using the identified features in each of a number of respective image sensor coordinate frames.

8 more elements

in a pre-runtime environment:
acquiring at least one image of a first view of a training object by at least one image sensor;
identifying a number of features of the training object in the acquired at least one image of the first view;
and
associating parameters to less than all of the identified features which define a physical relationship between the either the feature and at least one other feature or between the feature and the at least one image sensor;
and
determining a number of additional views to be obtained based at least in part on the number of image sensors acquiring at least one image and the number of features of the training object identified;
acquiring at least one image of a second view of the training object by the at least one image sensor;
and
identifying at least some of the number of features of the training object in the acquired at least one image of the second view;
and
in at least one of a pre-run time environment or a runtime environment, computationally determining a local model using the identified features in each of a number of respective image sensor coordinate frames.

9 more elements

Dependencies are inferred from the claim text.

Method and apparatus for machine-vision

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Method and apparatus for machine-vision

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Abstract

Claims39