Granted Patent B2

US 10,977,682 · App. 16/029,631 · Granted Apr 13, 2021

Inventors: Frank Zazza (New Rochelle, NY); Boris Vychodil (Portland, OR)

Assignee: Comscore, Inc.

G06Q30/0243G06Q30/02H04N21/4725H04N21/812

Abstract

Claims (102)

1. An automated method of classifying a product placement in a video using rule sets, each rule of the rule set including a value and one or more defining rule elements, the method comprising:

identifying, with image recognition software, a product in the video;

creating an attribute rule set with attribute values and attribute elements that define levels of audio visual prominence of the product in the video;

creating an integration rule set with integration values and integration elements where the integration elements define levels of integration of the product with video continuity;

partitioning the video at product scene changes to create product blocks;

for each product block, selecting an attribute value based on the attribute elements;

for each product block, selecting an integration value based on the integration elements; and

deriving an impact parameter for the video as a function of the selected attribute values and integration value.

2. The method of claim 1 , further comprising:

defining a time period as a finite period of time;

measuring segment duration of each segment; and

defining an occurrence value for each attribute level as one of:

the number of attribute values selected for each attribute level; or

the number of time periods in the durations of the segments assigned to each attribute level.

3. The method of claim 2 , further comprising:

defining an attentiveness factor as a ratio of the number of viewers of product placement to the number of viewers of commercial segments;

defining quality factors;

creating an awareness rule set with awareness values and awareness elements where the awareness elements define awareness levels of integration of the product with on-screen persona; and

deriving a quality parameter as a function of at least the occurrence value, the awareness level, the quality factors, and the attentiveness factor.

4. The method of claim 3 , further comprising:

defining an occurrence function; and

deriving the quality parameter as a function of the occurrence value, the awareness level, the attentiveness level, the quality factors and the occurrence function.

5. The method of claim 2 , further comprising:

defining an attentiveness factor as a ratio of the number of viewers of product placement to the number of viewers of commercial segments;

defining recall factors;

creating an awareness rule set with awareness values and awareness elements where the awareness elements define awareness levels of integration of the product with on-screen persona; and

deriving a recall parameter as a function of at least the occurrence value, the awareness level, the recall factors, and the attentiveness factor.

6. The method claim 5 , further comprising:

defining an occurrence function; and

deriving the recall parameter as a function of the occurrence value, the awareness level, the attentiveness level, the recall factors and the occurrence function.

7. The method of claim 1 , further comprising:

displaying a web page that includes:

a video portion that displays the video with the product placement; and

a qualitative data portion that displays integration values and attribute values.

8. A system for automatically classifying a product placement in a video using rule sets, each rule of the rule set including a value and one or more defining rule elements, the system comprising one or more processors connected to at least one storage device, the system being configured to:

identify, with image recognition software, a product in the video;

create an attribute rule set with attribute values and attribute elements that define levels of audio visual prominence of the product in the video;

create an integration rule set with integration values and integration elements where the integration elements define levels of integration of the product with video continuity;

partition the video at product scene changes to create product blocks;

for each product block, select an attribute value based on the attribute elements;

for each product block, select an integration value based on the integration elements; and

derive an impact parameter for the video as a function of the selected attribute values and integration value.

9. The system of claim 8 , wherein the system is further configured to:

define a time period as a finite period of time;

measure segment duration of each segment; and

define an occurrence value for each attribute level as one of:

the number of attribute values selected for each attribute level; or

the number of time periods in the durations of the segments assigned to each attribute level.

10. The system of claim 9 , wherein the system is further configured to:

define an attentiveness factor as a ratio of the number of viewers of product placement to the number of viewers of commercial segments;

define quality factors;

create an awareness rule set with awareness values and awareness elements where the awareness elements define awareness levels of integration of the product with on-screen persona; and

derive a quality parameter as a function of at least the occurrence value, the awareness level, the quality factors, and the attentiveness factor.

11. The system of claim 10 , wherein the system is further configured to:

define an occurrence function; and

derive the quality parameter as a function of the occurrence value, the awareness level, the attentiveness level, the quality factors and the occurrence function.

12. The system of claim 9 , wherein the system is further configured to:

define an attentiveness factor as a ratio of the number of viewers of product placement to the number of viewers of commercial segments;

define recall factors;

create an awareness rule set with awareness values and awareness elements where the awareness elements define awareness levels of integration of the product with on-screen persona; and

derive a recall parameter as a function of at least the occurrence value, the awareness level, the recall factors, and the attentiveness factor.

13. The system of claim 12 , wherein the system is further configured to:

define an occurrence function; and

derive the recall parameter as a function of the occurrence value, the awareness level, the attentiveness level, the recall factors and the occurrence function.

14. The system of claim 8 , wherein the system is further configured to:

display a web page that includes:

a video portion that displays the video with the product placement; and

a qualitative data portion that displays integration values and attribute values.

15. A storage device storing a computer program for automatically classifying a product placement in a video using rule sets, each rule of the rule set including a value and one or more defining rule elements, the computer program comprising one or more code segments that, when executed, cause one or more processors to:

identify, with image recognition software, a product in the video;

create an attribute rule set with attribute values and attribute elements that define levels of audio visual prominence of the product in the video;

create an integration rule set with integration values and integration elements where the integration elements define levels of integration of the product with video continuity;

partition the video at product scene changes to create product blocks;

for each product block, select an attribute value based on the attribute elements;

for each product block, select an integration value based on the integration elements; and

derive an impact parameter for the video as a function of the selected attribute values and integration value.

16. The storage device of claim 15 , wherein the computer program further comprises one or more code segments that, when executed, cause the one or more processors to:

define a time period as a finite period of time;

measure segment duration of each segment; and

define an occurrence value for each attribute level as one of:

the number of attribute values selected for each attribute level; or

the number of time periods in the durations of the segments assigned to each attribute level.

17. The storage device of claim 16 , wherein the computer program further comprises one or more code segments that, when executed, cause the one or more processors to:

define an attentiveness factor as a ratio of the number of viewers of product placement to the number of viewers of commercial segments;

define quality factors;

create an awareness rule set with awareness values and awareness elements where the awareness elements define awareness levels of integration of the product with on-screen persona; and

derive a quality parameter as a function of at least the occurrence value, the awareness level, the quality factors, and the attentiveness factor.

18. The storage device of claim 17 , wherein the computer program further comprises one or more code segments that, when executed, cause the one or more processors to:

define an occurrence function; and

derive the quality parameter as a function of the occurrence value, the awareness level, the attentiveness level, the quality factors and the occurrence function.

19. The storage device of claim 16 , wherein the computer program further comprises one or more code segments that, when executed, cause the one or more processors to:

define an attentiveness factor as a ratio of the number of viewers of product placement to the number of viewers of commercial segments;

define recall factors;

create an awareness rule set with awareness values and awareness elements where the awareness elements define awareness levels of integration of the product with on-screen persona; and

derive a recall parameter as a function of at least the occurrence value, the awareness level, the recall factors, and the attentiveness factor.

20. The storage device of claim 19 , wherein the computer program further comprises one or more code segments that, when executed, cause the one or more processors to:

define an occurrence function; and

derive the recall parameter as a function of the occurrence value, the awareness level, the attentiveness level, the recall factors and the occurrence function.

21. The storage device of claim 15 , wherein the computer program further comprises one or more code segments that, when executed, cause the one or more processors to:

display a web page that includes:

a video portion that displays the video with the product placement; and

a qualitative data portion that displays integration values and attribute values.

Assignments (9)