Object Recognition with 3D Models
First Claim
1. A computer-implemented method for training a view-based object recognition classifier, comprising:
- generating an initial training set of images, wherein an image in the initial training set is generated based on a three-dimensional model and a set of one or more rendering parameter values;
training the classifier using the initial training set;
determining the classifier'"'"'s accuracy;
determining a set of one or more local minima of the classifier'"'"'s output;
for each local minimum in the set of local minima;
determining a set of one or more rendering parameter values associated with the local minimum; and
generating an additional image based on the three-dimensional model and the determined set of one or more rendering parameter values;
training the classifier using the initial training set and the generated additional images.
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Abstract
An “active learning” method trains a compact classifier for view-based object recognition. The method actively generates its own training data. Specifically, the generation of synthetic training images is controlled within an iterative training process. Valuable and/or informative object views are found in a low-dimensional rendering space and then added iteratively to the training set. In each iteration, new views are generated. A sparse training set is iteratively generated by searching for local minima of a classifier'"'"'s output in a low-dimensional space of rendering parameters. An initial training set is generated. The classifier is trained using the training set. Local minima are found of the classifier'"'"'s output in the low-dimensional rendering space. Images are rendered at the local minima. The newly-rendered images are added to the training set. The procedure is repeated so that the classifier is retrained using the modified training set.
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Citations
20 Claims
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1. A computer-implemented method for training a view-based object recognition classifier, comprising:
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generating an initial training set of images, wherein an image in the initial training set is generated based on a three-dimensional model and a set of one or more rendering parameter values; training the classifier using the initial training set; determining the classifier'"'"'s accuracy; determining a set of one or more local minima of the classifier'"'"'s output; for each local minimum in the set of local minima; determining a set of one or more rendering parameter values associated with the local minimum; and generating an additional image based on the three-dimensional model and the determined set of one or more rendering parameter values; training the classifier using the initial training set and the generated additional images. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A machine-readable storage medium encoded with instructions that, when executed by a processor, cause the processor to perform a method for training a view-based object recognition classifier, comprising:
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generating an initial training set of images, wherein an image in the initial training set is generated based on a three-dimensional model and a set of one or more rendering parameter values; training the classifier using the initial training set; determining the classifier'"'"'s accuracy; determining a set of one or more local minima of the classifier'"'"'s output; for each local minimum in the set of local minima; determining a set of one or more rendering parameter values associated with the local minimum; and generating an additional image based on the three-dimensional model and the determined set of one or more rendering parameter values; training the classifier using the initial training set and the generated additional images. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A system for training a view-based object recognition classifier, comprising:
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a machine-readable storage medium encoded with machine-readable instructions for performing a method, the method comprising; generating an initial training set of images, wherein an image in the initial training set is generated based on a three-dimensional model and a set of one or more rendering parameter values; training the classifier using the initial training set; determining the classifier'"'"'s accuracy; determining a set of one or more local minima of the classifier'"'"'s output; for each local minimum in the set of local minima; determining a set of one or more rendering parameter values associated with the local minimum; and generating an additional image based on the three-dimensional model and the determined set of one or more rendering parameter values; training the classifier using the initial training set and the generated additional images; and a processor configured to execute the machine-readable instructions encoded on the machine-readable storage medium. - View Dependent Claims (18, 19, 20)
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Specification