Automatic person meta-data labeller

• US 20020048397A1
• Filed: 07/27/2001
• Published: 04/25/2002
• Est. Priority Date: 08/04/2000
• Status: Active Grant

• Current Assignee: Canon Kabushiki Kaisha (Canon Inc.)
• Original Assignee: Canon Kabushiki Kaisha (Canon Inc.)
• Inventors: Lloyd-Jones, Daniel John
• Granted Patent: US 7,054,481 B2
• Time in Patent Office: Days
• US Class Current: 382/165
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/20101 Interactive definition of point of interest, landmark or seed
• CPC Class Codes: G06T 7/0008 checking presence/absence
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/187 involving region growing; involving region merging; involving connected component labelling
• CPC Class Codes: G06T 7/90 Determination of colour characteristics

Abstract

A method 214 of identifying an object in a target image is disclosed, the method comprising steps of selecting 400 a part of the object having a distinctive color, searching 702 the target image for said part, and tagging 704 the target image if said part is found therein.

Claims

1. A method of identifying the presence of an object in a target image, said method comprising steps of:

selecting a part of said object, said part having a distinctive colour,

searching said target image for said part; and

tagging the target image if said part is found therein.

2. A method according to claim 1, wherein said object is a person, and said part of said object is a fashion accessory worn by the person.

3. A method according to claim 1, wherein said selecting step comprises manual provision of designation information, in relation to an indicative image, said designation information identifying said part of the object.

4. A method according to claim 1, wherein prior to said selecting step the method comprises defining said part of the object as an item in a menu, and wherein said selecting step comprises selecting said part from the menu.

5. A method according to claim 1, wherein:

the selecting step comprises an additional sub-step selecting another part of said object having another distinctive colour;

the searching step comprises an additional sub-step searching said target image for said other part of said object as well as for said part of said object; and

the tagging step comprises tagging the target image if both said part and said other part are found therein.

6. A method according to claim 1, wherein:

the searching step comprises an additional sub-step searching said target image for human skin colour as well as for said part of said image; and

the tagging step comprises tagging the target image if both said part and said skin colour are found therein.

7. A method according to claim 1, comprising, prior to the selecting step, additional steps of:

deriving meta-data for a core set of images;

grouping said core set into one or more event image sets dependent upon said meta-data; and

choosing a desired image set, comprising an indicative image and at least one target image, from said one or more event image sets.

8. A method according to claim 7, wherein said meta-data comprises time stamps associated with the images in the core set, and said grouping step comprises, in relation to an image in said core set, a sub-step of:

assigning said image to an event if an associated time stamp falls within a predetermined event time interval.

9. A method according to claim 7, wherein said meta-data comprises time stamps for the images in the core set, and said grouping step comprises, in relation to an image in said core set of images, a sub-step of:

assigning said image to an event if an associated time stamp can be clustered with time stamps associated with other images in said event.

10. A method according to claim 1, wherein said searching step comprises sub-steps of:

colour segmenting said target image into at least one colour region;

determining whether said distinctive colour matches said at least one colour region; and

flagging a presence of said object if a match is found.

11. A method according to claim 10, wherein:

said part, in addition to the distinctive colour, has at least one of a distinctive size attribute and a distinctive shape attribute;

said determining step comprises at least a further sub-step of

(a) determining whether a size of said region matches the distinctive size; and

(b) determining whether a shape of said region matches the distinctive shape; and

said flagging step comprises flagging a presence of said object if at least one of a colour match, a size match, and a shape match is found.

13. An apparatus according to claim 12, further comprising:

means for manual provision of designation information, in relation to an indicative image, to thereby identify said part of the object.

14. An apparatus according to claim 12, further comprising:

means for defining said part of the object as an item in a menu; and

means for selecting said part from the menu,

15. An apparatus according to claim 12, further comprising:

means for deriving meta-data for a core set of images;

means for grouping said core set into one or more event image sets dependent upon said meta-data; and

means for choosing a desired image set, comprising an indicative image and at least one target image, from said one or more event image sets.

16. An apparatus according to claim 12, further comprising

means for colour segmenting said target image into at least one colour region;

means for determining whether said distinctive colour matches said at least one colour region; and

means for flagging a presence of said object if a match is found.

19. A computer program according to claim 18, further comprising:

code for manual provision of designation information, in relation to an indicative image, to thereby identify said part of the object.

20. A computer program according to claim 18, further comprising:

code for defining said part of the object as an item in a menu; and

code for selecting said part from the menu.

21. A computer program according to claim 18, further comprising:

code for deriving meta-data for a core set of images;

code for grouping said core set into one or more event image sets dependent upon said meta-data; and

code for choosing a desired image set, comprising an indicative image and at least one target image, from said one or more event image sets.

22. A computer program according to claim 18, further comprising:

code for colour segmenting said target image into at least one colour region;

code for determining whether said distinctive colour matches said at least one colour region; and

code for flagging a presence of said object if a match is found.

12. An apparatus for identifying an object in a target image, said apparatus comprising:

means for selecting a part of said object, said part having a distinctive colour;

means for searching said target image for said part; and

means for tagging the target image if said part is found therein.

17. An apparatus for identifying an object in a target image, said apparatus comprising:

a memory for storing a program; and

a processor for executing the program, said program comprising;

code for selecting a part of said object, said part having a distinctive colour;

code for searching said target image for said part; and

code for tagging the target image if said part is found therein.

18. A computer program which is configured to make a computer execute a procedure to identify an object in a target image, said program comprising:

code for selecting a part of said object, said part having a distinctive colour,

code for searching said target image for said part; and

code for tagging the target image if said part is found therein.

23. A computer program product including a computer readable medium having recorded thereon a computer program which is configured to make a computer execute a procedure to identify an object in a target image, said program comprising:

code for selecting a part of said object, said part having a distinctive colour;

code for searching said target image for said part; and

code for tagging the target image if said part is found therein.