LEARNING APPARTUS, LEARNING METHOD, RECOGNITION APPARATUS, RECOGNITION METHOD, AND PROGRAM
First Claim
Patent Images
1. A learning apparatus comprising:
- first feature quantity calculating means for pairing a predetermined pixel and a different pixel in each of a plurality of learning images, which includes a learning image containing a target object to be recognized and a learning image not containing the target object, and calculating a first feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and
first discriminator generating means for generating a first discriminator for detecting the target object from an image by a statistical learning using a plurality of the first feature quantities.
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Abstract
A learning apparatus includes: first feature quantity calculating means for pairing a predetermined pixel and a different pixel in each of a plurality of learning images, which includes a learning image containing a target object to be recognized and a learning image not containing the target object, and calculating a first feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and first discriminator generating means for generating a first discriminator for detecting the target object from an image by a statistical learning using a plurality of the first feature quantities.
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Citations
13 Claims
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1. A learning apparatus comprising:
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first feature quantity calculating means for pairing a predetermined pixel and a different pixel in each of a plurality of learning images, which includes a learning image containing a target object to be recognized and a learning image not containing the target object, and calculating a first feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and first discriminator generating means for generating a first discriminator for detecting the target object from an image by a statistical learning using a plurality of the first feature quantities. - View Dependent Claims (2, 3, 4)
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5. A learning method comprising the steps of:
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pairing a predetermined pixel and a different pixel in each of a plurality of learning images, which includes a learning image containing a target object to be recognized and a learning image not containing the target object, and calculating a feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and generating a discriminator for detecting the target object from an image by a statistical learning using a plurality of the feature quantities.
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6. A program allowing a computer to execute a learning method including the steps of:
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pairing a predetermined pixel and a different pixel in each of a plurality of learning images, which includes a learning image containing a target object to be recognized and a learning image not containing the target object, and calculating a feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and generating a discriminator for detecting the target object from an image by a statistical learning using a plurality of the feature quantities.
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7. A recognition apparatus comprising:
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first feature quantity calculating means for pairing a predetermined pixel and a different pixel in an input image and calculating a first feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and detection means for detecting a target object from the input image, on the basis of the first feature quantity calculated by the first feature quantity calculating means, by the use of a first discriminator generated by statistical learning using a plurality of the first feature quantities obtained from a learning image including the target object to be recognized and a learning image not including the target object. - View Dependent Claims (8, 9)
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10. A recognition method comprising the steps of:
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pairing a predetermined pixel and a different pixel in an input image and calculating a feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and detecting a target object from the input image on the basis of the feature quantity calculated in the step of calculating the feature quantity by the use of a discriminator generated by statistical learning using a plurality of the feature quantities obtained from a learning image including the target object to be recognized and a learning image not including the target object.
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11. A program allowing a computer to execute a recognition method comprising the steps of:
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pairing a predetermined pixel and a different pixel in an input image and calculating a feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and detecting a target object from the input image on the basis of the feature quantity calculated in the step of calculating the feature quantity by the use of a discriminator generated by statistical learning using a plurality of the feature quantities obtained from a learning image including the target object to be recognized and a learning image not including the target object.
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12. A learning apparatus comprising:
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a first feature quantity calculator configured to pair a predetermined pixel and a different pixel in each of a plurality of learning images, which includes a learning image containing a target object to be recognized and a learning image not containing the target object, and to calculate a first feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and a first discriminator generator configured to generate a first discriminator for detecting the target object from an image by a statistical learning using a plurality of the first feature quantities.
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13. A recognition apparatus comprising:
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a first feature quantity calculator configured to pair a predetermined pixel and a different pixel in an input image and to calculate a first feature quantity of the pair by calculating a texture distance between an area including the predetermined pixel and an area including the different pixel; and a detector configured to detect a target object from the input image, on the basis of the first feature quantity calculated by the first feature quantity calculator, by the use of a first discriminator generated by statistical learning using a plurality of the first feature quantities obtained from a learning image including the target object to be recognized and a learning image not including the target object.
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Specification