Data difference guided image capturing

• US 9,183,465 B2
• Filed: 06/28/2013
• Issued: 11/10/2015
• Est. Priority Date: 07/28/2010
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Omer, Ido, Ofek, Eyal
• Primary Examiner(s): Le, Vu
• Assistant Examiner(s): WOLDEMARIAM, AKLILU K
• Application Number:
  US13/929,962
• Publication Number:
  US 20130287307A1
• Time in Patent Office: 865 Days
• Field of Search: 382/203, 382/218, 382/103, 382/110, 382/128, 382/154, 707/741, 707/728, 707/2, 707/8, 707/9, 707/203, 348/46, 348/144, 348/158, 348/231
• US Class Current: 1/1
• CPC Class Codes: G06V 10/75 Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
• CPC Class Codes: G06V 20/13 Satellite images

Abstract

Methods and apparatuses are disclosed. Previously stored images of one or more geographic areas may be viewed by online users. A new low-resolution image may be acquired and aspects of the new low-resolution image may be compared with a corresponding one of the previously stored images to determine an amount of change. A determination may be made regarding whether to acquire a new high-resolution image based on the determined amount of change and a freshness score associated with the one of the previously stored images. In another embodiment, a new image may be captured and corresponding location data may be obtained. A corresponding previously stored image may be obtained and compared with the new image to determine an amount of change. The new image may be uploaded to a remote computing device based on the determined amount of change and a freshness score of the previously stored image.

Claims

1. A method, comprising:

resolving a freshness score for an acquired high-resolution aerial image of a geographic area, the score indicative of a probability that a new high-resolution image of the geographic area is needed so as to update coverage of the geographic area;

identifying a recently acquired low-resolution aerial image of the geographic area;

determining an amount of change in the geographic area since the high-resolution image was acquired by comparing, by a computing device, one or more aspects of the identified recently acquired low-resolution aerial image and of the stored high-resolution aerial image; and

deciding to update the coverage of the geographic area by ordering a new high-resolution aerial image, based on the freshness score and the determined amount of change.

2. The method of claim 1, further comprising resolving a synthetic high-resolution image from the obtained recent low-resolution aerial image, when a result of the deciding is affirmative.

3. The method of claim 1, wherein the determining an amount of change further comprises removing person-sized objects from the one or more aspects that are compared.

4. The method of claim 1, wherein the one or more aspects reflect an amount of change to static buildings.

5. The method of claim 1, wherein the determining an amount of change further comprises:

recovering text from the captured image data; and

comparing the recovered text from the captured image data with known data.

6. A method, comprising:

resolving a freshness score for an acquired high-resolution image of a location, the score indicative of a probability that a new high-resolution image of the location is needed so as to update coverage of the location;

identifying a recently acquired low-resolution image of the location;

determining an amount of change in the location since the high-resolution image was acquired by comparing, by a computing device, at least one aspect of the identified recently acquired low-resolution image and at least one aspect of the stored high-resolution image; and

deciding to update the coverage of the location by ordering a new high-resolution image, based on the freshness score and the determined amount of change.

7. The method of claim 6, wherein at least one of the recently acquired low-resolution image and the acquired high-resolution image is an aerial image.

8. The method of claim 6, wherein at least one of the recently acquired low-resolution image and the acquired high-resolution image is a street level image.

9. The method of claim 6, wherein at least one of the recently acquired low-resolution image and the acquired high-resolution image is an online image.

10. The method of claim 6, wherein the one or more aspects is a color distribution at the location, a spectral reflectance at the location, or textures at the location.

11. The method of claim 6, wherein the one or more aspects reflects man-made changes at the location.

12. The method of claim 11, wherein the one or more aspects includes a change in an appearance of a road at the location, a change in appearance of buildings at the location, or agricultural changes at the location.

13. The method of claim 6, wherein the determining comprises analyzing non-image data.

14. The method of claim 13, wherein the non-image data includes data from articles concerning new construction at the location, articles concerning demolition at the location, or articles concerning changes in land use at the location.

15. The method of claim 6, wherein the determining an amount of change includes analyzing non-image data, the non-image data having an associated summation value that is a sum of respective values associated with members of a set of various types of changes at the location.

16. A computing device comprising:

at least one processor;

a bus; and

a memory connected to the at least one processor via the bus;

the memory including instructions for the at least one processor to perform a method comprising;

resolving a freshness score for an acquired high-resolution aerial image of a geographic area, the score indicative of a probability that a new high-resolution image of the geographic area is needed so as to update coverage of the geographic area;

identifying a recently acquired low-resolution aerial image of the geographic area;

determining an amount of change in the geographic area since the high-resolution image was acquired by comparing, by a computing device, one or more aspects of the identified recently acquired low-resolution aerial image and of the stored high-resolution aerial image; and

deciding to update the coverage of the geographic area by ordering a new high-resolution aerial image, based on the freshness score and the determined amount of change.

17. A computing device comprising:

at least one processor;

a bus; and

a memory connected to the at least one processor via the bus, the memory including instructions for the at least one processor to perform a method comprising;

resolving a freshness score for an acquired high-resolution image of a location, the score indicative of a probability that a new high-resolution image of the location is needed so as to update coverage of the location;

identifying a recently acquired low-resolution image of the location;

determining an amount of change in the location since the high-resolution image was acquired by comparing, by a computing device, at least one aspect of the identified recently acquired low-resolution image and at least one aspect of the stored high-resolution image; and

deciding to update the coverage of the location by ordering a new high-resolution image, based on the freshness score and the determined amount of change.