Determining the Uniqueness of a Model for Machine Vision
First Claim
1. A computerized method for determining a quality metric of a model of an object in a machine vision application, the method comprising:
- receiving a training image and a first set of model parameters;
generating a first model of an object;
generating a second model of the object based on the training image and a second set of model parameters modified from the first set of model parameters;
determining a set of poses that represent possible instances of the second model in the training image; and
computing a quality metric of the first model based on an evaluation of the set of poses with respect to the training image.
1 Assignment
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Accused Products
Abstract
Described are methods and apparatuses, including computer program products, for determining model uniqueness with a quality metric of a model of an object in a machine vision application. Determining uniqueness involves receiving a training image and a first set of model parameters, generating a first model of an object, generating a second model of the object based on the training image and a second set of model parameters modified from the first set of model parameters, determining a set of poses that represent possible instances of the second model in the training image, and computing a quality metric of the first model based on an evaluation of the set of poses with respect to the training image.
13 Citations
18 Claims
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1. A computerized method for determining a quality metric of a model of an object in a machine vision application, the method comprising:
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receiving a training image and a first set of model parameters; generating a first model of an object; generating a second model of the object based on the training image and a second set of model parameters modified from the first set of model parameters; determining a set of poses that represent possible instances of the second model in the training image; and computing a quality metric of the first model based on an evaluation of the set of poses with respect to the training image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A computer program product, tangibly embodied in a machine-readable storage device, the computer program product including instructions being operable to cause a data processing apparatus to:
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receive a training image and a first set of model parameters; generate a first model of an object; generate a second model of the object based on the training image and a second set of model parameters modified from the first set of model parameters; determine a set of poses that represent possible instances of the second model in the training image; and compute a quality metric of the first model based on an evaluation of the set of poses with respect to the training image.
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17. A system for determining a quality metric of a model of an object in a machine vision application, the system comprising:
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interface means for receiving a training image and a first set of model parameters; model generating means for generating a first model of an object; model generating means for generating a second model of the object based on the training image and a second set of model parameters modified from the first set of model parameters; processor means for determining a set of poses that represent possible instances of the second model in the training image; and processor means for computing a quality metric of the first model based on an evaluation of the set of poses with respect to the training image.
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18. A machine vision system for determining a quality metric of a model of an object in a machine vision application, the system comprising:
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an interface for receiving a training image and a first set of model parameters; a model generating module For generating a first model of an object and for generating a second model of the object based on the training image and a second set of model parameters modified from the first set of model parameters; a run-time module for determining a set of poses that represent possible instances of the second model in the training image; and a quality-metric module for computing a quality metric of the first model based on an evaluation of the set of poses with respect to the training image.
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Specification