LEARNING APPARTUS, LEARNING METHOD, RECOGNITION APPARATUS, RECOGNITION METHOD, AND PROGRAM

• US 20090202145A1
• Filed: 12/04/2008
• Published: 08/13/2009
• Est. Priority Date: 12/07/2007
• Status: Abandoned Application

• Current Assignee: Sony Corporation (Sony Group Corp.)
• Original Assignee: Sony Corporation (Sony Group Corp.)
• Inventors: YOKONO, Jun, Hasegawa, Yuichi
• Application Number:
  US12/328,318
• Publication Number:
  US 20090202145A1
• Time in Patent Office: Days
• US Class Current: 382/160
• CPC Class Codes: G06F 18/253 of extracted features
• CPC Class Codes: G06V 10/806 of extracted features
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands

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.

Claims

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.

2. The learning apparatus according to claim 1, further comprising:

second feature quantity calculating means for making a calculation of extracting an outline from each of the plurality of learning images and generating a second feature quantity from the calculation result;

second discriminator generating means for generating a second discriminator for detecting the target object from the image by a statistical learning using a plurality of the second feature quantities; and

third discriminator generating means for combining the first discriminator and the second discriminator to generate a third discriminator for detecting the target object from the image.

3. The learning apparatus according to claim 2, wherein the third discriminator generating means generates the third discriminator by linearly combining the first discriminator and the second discriminator.

4. The learning apparatus according to claim 1, further comprising second feature quantity calculating means for making a calculation of extracting an outline from each of the plurality of learning images and generating a second feature quantity from the calculation result,

wherein the first discriminator generating means generates the first discriminator by a statistical learning using the plurality of first feature quantities and the plurality of second feature quantities.

5. A learning method comprising the steps of:

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.

6. A program allowing a computer to execute a learning method including the steps of:

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.

7. A recognition apparatus comprising:

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.

8. The recognition apparatus according to claim 7, further comprising second feature quantity calculating means for making a calculation of extracting an outline from the input image to generate a second feature quantity from the calculation result,

wherein the detection means detects the target object from the input image on the basis of the first feature quantity calculated by the first feature quantity calculating means and the second feature quantity calculated by the second feature quantity calculating means, by the use of a third discriminator obtained by combining the first discriminator with a second discriminator generated by statistical learning using a plurality of the second feature quantities, which are obtained from the learning image including the target object to be recognized and the learning image not including the target object.

9. The recognition apparatus according to claim 7, further comprising second feature quantity calculating means for making a calculation of extracting an outline from the input image to generate a second feature quantity from the calculation result,

wherein the detection means detects the target object from the input image on the basis of the first feature quantity calculated by the first feature quantity calculating means and the second feature quantity calculated by the second feature quantity calculating means, by the use of the first discriminator generated by statistical learning using the plurality of first feature quantities and the plurality of the second feature quantities, which are obtained from the learning image including the target object to be recognized and the learning image not including the target object.

10. A recognition method comprising the steps of:

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.

11. A program allowing a computer to execute a recognition method comprising the steps of:

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.

12. A learning apparatus comprising:

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.

13. A recognition apparatus comprising:

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.