Scene Classification Apparatus and Scene Classification Method

• US 20080232696A1
• Filed: 03/20/2008
• Published: 09/25/2008
• Est. Priority Date: 03/23/2007
• Status: Abandoned Application

• Current Assignee: Seiko Epson Corporation (Seiko Group)
• Original Assignee: Seiko Epson Corporation (Seiko Group)
• Inventors: KASAHARA, Hirokazu, KASAI, Tsuneo, MATSUMOTO, Kaori
• Application Number:
  US12/052,632
• Publication Number:
  US 20080232696A1
• Time in Patent Office: Days
• US Class Current: 382/224
• CPC Class Codes: G06F 18/2411 based on the proximity to a decision surface, e.g. support vector machines
• CPC Class Codes: G06V 10/50 by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis
• CPC Class Codes: G06V 20/10 Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59

Abstract

A scene classification apparatus includes: a characteristic amount obtaining section that obtains a partial characteristic amount indicating a characteristic of a partial image that is a portion of a classification-target image; a partial classification section that classifies, based on the partial characteristic amount, whether or not the partial image belongs to a predetermined scene; a detection section that detects the number of the partial images classified as belonging to the predetermined scene; and a decision section that decides, according to the number of the partial images detected by the detection section, whether or not the classification-target image belongs to the predetermined scene.

Claims

1. A scene classification apparatus, comprising:

a characteristic amount obtaining section that obtains a partial characteristic amount indicating a characteristic of a partial image that is a portion of a classification-target image;

a partial classification section that classifies, based on the partial characteristic amount obtained by the characteristic amount obtaining section, whether or not the partial image belongs to a predetermined scene;

a detection section that detects the number of the partial images classified by the partial classification section as belonging to the predetermined scene; and

a decision section that decides, according to the number of the partial images detected by the detection section, whether or not the classification-target image belongs to the predetermined scene.

2. A scene classification apparatus according to claim 1, wherein:

if the number of the partial images detected by the detection section exceeds a predetermined threshold,

the decision section decides that the classification-target image belongs to the predetermined scene.

3. A scene classification apparatus according to claim 2, wherein:

the detection section detects the number of remaining images that has not been classified by the partial classification section, among all of the partial images obtained from the classification-target image, and

if a sum of the number of the remaining images detected by the detection section and the number of the partial images belonging to the predetermined scene does not reach the predetermined threshold,

the decision section decides that the classification-target image does not belong to the predetermined scene.

4. A scene classification apparatus according to claim 2, wherein:

the partial classification section is provided for each type of the predetermined scene to be classified.

5. A scene classification apparatus according to claim 4, wherein:

the predetermined threshold is set for each of a plurality of the predetermined scenes.

6. A scene classification apparatus according to claim 4, wherein:

if in a classification with a first partial classification section, it cannot be decided that the classification-target image belongs to a first predetermined scene,

in a classification with a partial classification section other than the first partial classification section, the decision section decides whether or not the classification-target image belongs to a predetermined scene other than the first predetermined scene.

7. A scene classification apparatus according to claim 1, wherein:

the partial classification section obtains probability information that indicates a probability that the partial image belongs to the predetermined scene, from the partial characteristic amount corresponding to the partial image, and

classifies, based on the probability information, whether or not the partial image belongs to the predetermined scene.

8. A scene classification apparatus according to claim 7, wherein:

the partial classification section is a support vector machine that obtains the probability information from the partial characteristic amount.

9. A scene classification apparatus according to claim 1, wherein:

the characteristic amount obtaining section obtains an overall characteristic amount that indicates a characteristic of the classification-target image,

based on the partial characteristic amount and the overall characteristic amount that are obtained by the characteristic amount obtaining section, the partial classification section classifies whether or not the partial image is the predetermined scene.

10. A scene classification method, comprising:

obtaining a partial characteristic amount that indicates a characteristic of a partial image that is a portion of a classification-target image;

classifying, based on the obtained partial characteristic amount, whether or not the partial image belongs to a predetermined scene;

detecting the number of the partial images classified as belonging to the predetermined scene; and

judging, according to the number of the detected partial images, whether or not the classification-target image belongs to the predetermined scene.

11. A scene classification apparatus, comprising:

a storage section that stores at least either one of presence probability information indicating, for each of partial regions, a presence probability that a characteristics of the predetermined scene appear, and presence-probability ranking information indicating an order of the presence probability for a plurality of the partial regions, the partial regions being obtained by dividing an entire region of an image belonging to a predetermined scene;

a characteristic amount obtaining section that obtains a partial characteristic amount indicating a characteristic of a partial image that is a portion of a classification-target image and that corresponds to the partial region;

a partial evaluation section that evaluates, based on the partial characteristic amount obtained by the characteristic amount obtaining section, whether or not the partial image belongs to the predetermined scene, in a descending order by the presence probability based on at least either one of the presence probability information and the presence-probability ranking information that are read out from the storage section; and

a decision section that decides, according to an evaluation value obtained by the partial evaluation section, whether or not the classification-target image belongs to the predetermined scene.

12. A scene classification apparatus according to claim 11, wherein:

the partial evaluation section classifies, based on the partial characteristic amount, whether or not the partial image belongs to the predetermined scene, and

if the number of the partial images classified by the partial evaluation section as belonging to the predetermined scene exceeds a predetermined threshold, the decision section decides that the classification-target image belongs to the predetermined scene.

13. A scene classification apparatus according to claim 12, wherein:

at least either one of the presence probability information and the presence-probability ranking information is stored in the storage section for each type of the predetermined scene to be classified.

14. A scene classification apparatus according to claim 13, wherein:

the partial evaluation section is provided for each type of the predetermined scene, and

each of the partial evaluation sections classifies the partial image in a descending order by the presence probability of the predetermined scene, based on at least either one of the presence probability information and the presence-probability ranking information that are read out from the storage section corresponding to the predetermined scene to be classified.

15. A scene classification apparatus according to claim 14, wherein:

the predetermined threshold is set for each of a plurality of the predetermined scenes, and

if the number of the partial images classified by the partial evaluation section as belonging to a corresponding one of the predetermined scenes exceeds the predetermined threshold set to the corresponding predetermined scene, the decision section decides that the classification-target image belongs to that predetermined scene.

16. A scene classification apparatus according to claim 14, wherein:

if it cannot be decided, based on a classification with a first partial evaluation section, that the classification-target image belongs to a first predetermined scene,

the decision section classifies, with a partial evaluation section other than the first partial evaluation section, whether or not the partial image belongs to a predetermined scene other than the first predetermined scene.

17. A scene classification apparatus according to claim 11, wherein:

the characteristic amount obtaining section obtains an overall characteristic amount that indicates a characteristic of the classification-target image, and

the partial evaluation section evaluates, based on the partial characteristic amount and the overall characteristic amount that are obtained by the characteristic amount obtaining section, whether or not the partial image belongs to the predetermined scene, in a descending order by the presence probability based on at least either one of the presence probability information and the presence-probability ranking information that are read out from the storage section.