IP Library Granted Patent US 9,378,509
Granted Patent B2
US 9,378,509 · App. 13/829,644 · Granted Jun 28, 2016

Methods, apparatus, and articles of manufacture to measure geographical features using an image of a geographical location

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Quick Facts
Patent No.
US 9,378,509
App. No.
13/829,644
Granted
Jun 28, 2016
Kind
B2
Abstract

Methods, apparatus, and articles of manufacture to measure geographical features using an image of a geographical location are disclosed. An example method includes identifying first features of a first open market from a first image of a first geographic area, identifying second features of a second image of a second geographic area, comparing the first features to the second features, and identifying a second open market in the second image based on the comparison.

Claims (41)

1. A method, comprising:

identifying, by executing an instruction with a processor, first features of a first open market from a first image of a first geographic area;

identifying, by executing an instruction with the processor, second features of a second image of a second geographic area;

comparing the first features to the second features by executing an instruction with the processor;

identifying, by executing an instruction with the processor, additional open markets in the second image based on the comparison;

determining, by executing an instruction with the processor, first characteristics of the additional open markets based on the comparison of the first features to the second features and corresponding second characteristics of the first open market, the first characteristics including at least one of a) numbers of stores in the additional open markets, b) physical sizes of the additional open markets, c) whether the additional open markets are in previously enumerated areas or previously unenumerated areas, or d) trade areas of the additional open markets;

modifying, by executing an instruction with the processor, a sampling area in the second geographic area to be physically sampled to include in the sampling area at least a subset of the additional open markets in the second geographic area based on the first characteristics; and

providing the modified sampling area to a sampler for physical sampling of the second geographic area according to the modified sampling area to determine a number of stores in the second geographic area, the physical sampling including determining a retail characteristic of the modified sampling area.

2. The method of claim 1 , further including training a feature locator using the first features and the first image.

3. The method of claim 1 , wherein identifying the first features includes using a scale-invariant feature transform, a Bag of Words for Computer Vision model, or interest point descriptors.

4. The method of claim 1 , further including identifying a trade area for a first one of the additional open markets, identifying the trade area including determining the trade area to have at least a threshold number of customers of the first one of the additional open markets.

5. The method of claim 1 , further including predicting a first number of stores in a first one of the additional open markets based on an area of at least a portion of the second image.

6. The method of claim 1 , further including ranking the additional open markets relative to a third open market in a third image.

7. The method of claim 1 , wherein the first and second images include aerial images.

8. A method of claim 1 , further including estimating a growth rate of a first one of the additional open markets based on the first features.

9. An apparatus, comprising:

an image divider to define a first image of a first geographic area and a second image of a second geographic area;

a feature locator to identify first features of a first open market from the first image and to identify second features of a portion of the second image;

a zone analyzer to:

compare the first features to the second features and identify additional open markets in the portion of the second image based on the comparison; and

determine first characteristics of the additional open markets based on the comparison of the first features to the second features and corresponding second characteristics of the first open market, the first characteristics including at least one of a) numbers of stores in the additional open markets, b) physical sizes of the additional open markets, c) whether the additional open markets are in previously enumerated areas or previously unenumerated areas, or d) trade areas of the additional open markets; and

a sample stratifier to:

modify a sampling area in the second geographic area to be physically sampled to include in the sampling area at least a subset of the additional open markets in the second geographic area based on the first characteristics; and

provide the modified sampling area to a sampler for physical sampling of the second geographic area according to the modified sampling area to determine a number of stores in the second geographic area, the physical sampling including determining a retail characteristic of the modified sampling area.

10. The apparatus of claim 9 , further including a retail trade area identifier to identify a retail trade area of a first one of the additional open markets, the retail trade area including at least a threshold amount of customers of the -a first one of the additional open markets.

11. The apparatus of claim 9 , wherein the feature locator includes a scale invariant feature transform locator to identify the first features using a scale invariant feature transform.

12. The apparatus of claim 9 , wherein the zone analyzer is to rank the first open market relative to the additional open markets.

13. The apparatus of claim 9 , wherein the zone analyzer is to estimate the numbers of stores in the additional open markets of stores in the additional open markets.

14. The apparatus of claim 9 , wherein the zone analyzer is to estimate a total number of open markets in the second geographic area.

15. A tangible computer readable medium comprising computer readable instructions which, when executed, cause a processor to at least:

identify first features of a first open market from a first image of a first geographic area;

identify second features of a second image of a second geographic area;

compare the first features to the second features;

identify additional open markets in the second image based on the comparisons;

determine first characteristics of the additional open markets based on the comparison of the first features to the second features and corresponding second characteristics of the first open market, the first characteristics including at least one of a) numbers of stores in the additional open markets, b) physical sizes of the additional open markets, c) whether the additional open markets are in previously enumerated areas or previously unenumerated areas, or d) trade areas of the additional open markets;

modify a sampling area in the second geographic area to be physically sampled to include in the sampling area at least a subset of the additional open markets in the second geographic area based on the first characteristics; and

provide the modified sampling area to a sampler for physical sampling of the second geographic area according to the modified sampling area to determine a number of stores in the second geographic area, the physical sampling including determining a retail characteristic of the modified sampling area.

16. The tangible computer readable medium of claim 15 , wherein the instructions are further to cause the processor to train a feature locator using the first features and the first image.

17. The tangible computer readable medium of claim 15 , wherein the instructions are to cause the processor to identify the first features using a scale-invariant feature transform, a Bag of Words for Computer Vision model, or interest point descriptors.

18. The tangible computer readable medium of claim 15 , wherein the instructions are further to cause the processor to identify the trade areas of the additional open markets based on physical distances between the first and additional open markets.

19. The tangible computer readable medium of claim 15 , wherein the instructions are further to cause the processor to estimate a total number of open markets in the second geographic area based on located open markets in the second geographic area, the located open markets including the additional open markets.

Assignments (9)
RELEASE (REEL 054066 / FRAME 0064) Recorded May 11, 2023
From: CITIBANK, N.A.
To: GRACENOTE, INC.; A. C. NIELSEN COMPANY, LLC; EXELATE, INC.; GRACENOTE MEDIA SERVICES, LLC; THE NIELSEN COMPANY (US), LLC; NETRATINGS, LLC
Reel/Frame 063605/0001 →
RELEASE (REEL 053473 / FRAME 0001) Recorded May 11, 2023
From: CITIBANK, N.A.
To: A. C. NIELSEN COMPANY, LLC; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE MEDIA SERVICES, LLC; THE NIELSEN COMPANY (US), LLC; NETRATINGS, LLC
Reel/Frame 063603/0001 →
SECURITY INTEREST Recorded May 8, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: ARES CAPITAL CORPORATION
Reel/Frame 063574/0632 →
SECURITY INTEREST Recorded Apr 28, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: CITIBANK, N.A.
Reel/Frame 063561/0381 →
SECURITY AGREEMENT Recorded Jan 31, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: BANK OF AMERICA, N.A.
Reel/Frame 063560/0547 →
RELEASE (REEL 037172 / FRAME 0415) Recorded Oct 13, 2022
From: CITIBANK, N.A.
To: THE NIELSEN COMPANY (US), LLC
Reel/Frame 061750/0221 →
CORRECTIVE ASSIGNMENT TO CORRECT THE PATENTS LISTED ON SCHEDULE 1 RECORDED ON 6-9-2020 PREVIOUSLY RECORDED ON REEL 053473 FRAME 0001. ASSIGNOR(S) HEREBY CONFIRMS THE SUPPLEMENTAL IP SECURITY AGREEMENT. Recorded Oct 7, 2020
From: A.C. NIELSEN (ARGENTINA) S.A.; A.C. NIELSEN COMPANY, LLC; ACN HOLDINGS INC.; ACNIELSEN CORPORATION; ACNIELSEN ERATINGS.COM; AFFINNOVA, INC.; ART HOLDING, L.L.C.; ATHENIAN LEASING CORPORATION; CZT/ACN TRADEMARKS, L.L.C.; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; NETRATINGS, LLC; NIELSEN AUDIO, INC.; NIELSEN CONSUMER INSIGHTS, INC.; NIELSEN CONSUMER NEUROSCIENCE, INC.; NIELSEN FINANCE CO.; NIELSEN FINANCE LLC; NIELSEN INTERNATIONAL HOLDINGS, INC.; NIELSEN MOBILE, LLC; NMR INVESTING I, INC.; TCG DIVESTITURE INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC; VIZU CORPORATION; VNU MARKETING INFORMATION, INC.; NMR LICENSING ASSOCIATES, L.P.; NIELSEN HOLDING AND FINANCE B.V.; THE NIELSEN COMPANY B.V.; VNU INTERNATIONAL B.V.
To: CITIBANK, N.A
Reel/Frame 054066/0064 →
SUPPLEMENTAL SECURITY AGREEMENT Recorded Jun 9, 2020
From: A. C. NIELSEN COMPANY, LLC; ACN HOLDINGS INC.; ACNIELSEN CORPORATION; ACNIELSEN ERATINGS.COM; AFFINNOVA, INC.; ART HOLDING, L.L.C.; ATHENIAN LEASING CORPORATION; CZT/ACN TRADEMARKS, L.L.C.; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; NETRATINGS, LLC; NIELSEN AUDIO, INC.; NIELSEN CONSUMER INSIGHTS, INC.; NIELSEN CONSUMER NEUROSCIENCE, INC.; NIELSEN FINANCE CO.; NIELSEN FINANCE LLC; NIELSEN INTERNATIONAL HOLDINGS, INC.; NIELSEN MOBILE, LLC; NIELSEN UK FINANCE I, LLC; NMR INVESTING I, INC.; TCG DIVESTITURE INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC; VIZU CORPORATION; VNU MARKETING INFORMATION, INC.; NMR LICENSING ASSOCIATES, L.P.; NIELSEN HOLDING AND FINANCE B.V.; THE NIELSEN COMPANY B.V.; VNU INTERNATIONAL B.V.
To: CITIBANK, N.A.
Reel/Frame 053473/0001 →
SUPPLEMENTAL IP SECURITY AGREEMENT Recorded Nov 30, 2015
From: THE NIELSEN COMPANY ((US), LLC
To: CITIBANK, N.A., AS COLLATERAL AGENT FOR THE FIRST LIEN SECURED PARTIES
Reel/Frame 037172/0415 →