Identifying and Generating Color and Texture Video Cohorts Based on Video Input

• US 20100150457A1
• Filed: 12/11/2008
• Published: 06/17/2010
• Est. Priority Date: 12/11/2008
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kraemer, James R., Angell, Robert Lee, Friedlander, Robert R., Patnaik, Yasodhar, Borger, Sergio
• Granted Patent: US 8,749,570 B2
• Time in Patent Office: Days
• US Class Current: 382/224
• CPC Class Codes: G06V 10/56 relating to colour
• CPC Class Codes: G06V 10/60 relating to illumination properties, e.g. using a reflectance or lighting model

Abstract

A computer implemented method, apparatus, and computer program product for generating video based cohorts. Digital video data is processed to identify a set of color and texture based attributes associated with the set of objects. The digital video data comprises metadata describing the set of objects. The set of color and texture based attributes are analyzed using cohort criteria to form a result. The cohort criteria specify attributes that are associated with members of a given cohort. A set of cohorts is generated based on the result. Each cohort in the set of cohorts comprises a subset of objects from the set of objects that share at least one color and texture based attribute in common.

Claims

1. A computer implemented method for generating video based cohorts, the computer implemented method comprising:

processing digital video data, by a video analysis engine, to identify a set of color and texture based attributes associated with the set of objects, wherein the digital video data comprises metadata describing the set of objects;

analyzing the set of color and texture based attributes using cohort criteria to form a result, wherein the cohort criteria specify attributes that are associated with members of a given cohort; and

generating a set of cohorts based on the result, wherein each cohort in the set of cohorts comprises a subset of objects from the set of objects that share at least one color and texture based attribute in common.

2. The computer implemented method of claim 1 wherein the color and texture attributes comprises an identification of a color of a portion of an object in the set of objects.

3. The computer implemented method of claim 1 wherein the color and texture attributes comprises properties of a color associated with a portion of an object in the set of objects.

4. The computer implemented method of claim 1 wherein the color and texture attributes comprises an identification of a pattern of colors associated with an object in the set of objects.

5. The computer implemented method of claim 1 wherein the color and texture attributes comprises an identification of a texture associated with a portion of a surface of an object in the set of objects.

6. The computer implemented method of claim 1 wherein the color and texture attributes comprises an identification of a shadow associated with a portion of an object in the set of objects.

7. The computer implemented method of claim 1 wherein the color and texture attributes comprises identification markings associated with a portion of an object in the set of objects.

8. The computer implemented method of claim 7 wherein the identification markings comprises at least one of a name on an identification badge, a license plate number, a label on the object, a serial number, a bar code, a lot number, a model number, and a product name.

9. The computer implemented method of claim 1 further comprising:

receiving the set of cohorts by an inference engine; and

processing the set of cohorts by the inference engine, wherein the inference engine uses the set of video based cohorts to generate a set of inferences.

10. The computer implemented method of claim 1 wherein analyzing the set of video based attributes using the cohort criteria to form the result further comprises:

analyzing the color and texture based attributes using a set of color patterns, by a cohort generation engine, to form the result.

11. The computer implemented method of claim 1 wherein analyzing the set of video based attributes using the cohort criteria to form the result further comprises:

analyzing the video based attributes using cohort constraints to form the result, wherein cohort constraints specify attributes that are absent from members of a given cohort in the set of video cohorts.

12. A computer program product for generating video cohort data, the computer program product comprising:

a computer usable medium having computer usable program code embodied therewith, the computer usable program code comprising;

computer usable program code configured to process digital video data, by a video analysis engine, to identify a set of color and texture based attributes associated with the set of objects, wherein the digital video data comprises metadata describing the set of objects;

computer usable program code configured to analyze the set of color and texture based attributes using cohort criteria to form a result, wherein the cohort criteria specify attributes that are associated with members of a given cohort; and

computer usable program code configured to generate a set of cohorts based on the result, wherein each cohort in the set of cohorts comprises a subset of objects from the set of objects that share at least one color and texture based attribute in common.

13. The computer program product of claim 12 wherein the color and texture attributes comprises an identification of a color of a portion of an object in the set of objects.

14. The computer program product of claim 12 wherein the color and texture attributes comprises properties of a color associated with a portion of an object in the set of objects.

15. The computer program product of claim 12 wherein the color and texture attributes comprises an identification of a pattern of colors associated with a portion of an object in the set of objects.

16. The computer program product of claim 12 wherein the color and texture attributes comprises an identification of a texture associated with a portion of a surface of an object in the set of objects.

17. The computer program product of claim 12 further comprising:

computer usable program code configured to receive the set of cohorts by an inference engine; and

computer usable program code configured to process the set of cohorts by the inference engine, wherein the inference engine uses the set of to generate a set of inferences.

18. An apparatus comprising:

a bus system;

a communications system coupled to the bus system;

a memory connected to the bus system, wherein the memory includes computer usable program code; and

a processing unit coupled to the bus system, wherein the processing unit executes the computer usable program code to process digital video data, by a video analysis engine, to identify a set of color and texture based attributes associated with the set of objects, wherein the digital video data comprises metadata describing the set of objects;

analyze the set of color and texture based attributes using cohort criteria to form a result, wherein the cohort criteria specify attributes that are associated with members of a given cohort; and

generate a set of cohorts based on the result, wherein each cohort in the set of cohorts comprises a subset of objects from the set of objects that share at least one color and texture based attribute in common.

19. The apparatus of 18 wherein the processing unit executes the computer usable program code to receive the set of cohorts by an inference engine and process the set of cohorts by the inference engine, wherein the inference engine uses the set of cohorts to generate a set of inferences.

20. A video cohort generation system comprising:

a set of cameras, wherein the set of cameras captures a set of images of a plurality of objects;

a digital video analysis engine, wherein the digital video analysis engine processes digital video data, by a video analysis engine, to identify a set of color and texture based attributes associated with the set of objects, wherein the digital video data comprises metadata describing the set of objects; and

a cohort generation engine, wherein the cohort generation engine analyzes the set of color and texture based attributes using cohort criteria to form a result, wherein the cohort criteria specify attributes that are associated with members of a given cohort; and

generates a set of cohorts based on the result, wherein each cohort in the set of cohorts comprises a subset of objects from the set of objects that share at least one color and texture based attribute in common.