Managing performance of human review of media data

• US 10,438,152 B1
• Filed: 01/25/2008
• Issued: 10/08/2019
• Est. Priority Date: 01/25/2008
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Deflaux, Nicole A., Blair, James R., Goo, Jang Han, Chien, Mark, Cabrera, Luis Felipe, Hussein, Mohamed Reza
• Primary Examiner(s): Goldberg, Ivan R
• Application Number:
  US12/020,469
• Time in Patent Office: 4,274 Days
• Field of Search: None
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/387 using geographical or spatial information, e.g. location
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06Q 10/06316 Sequencing of tasks or work
• CPC Class Codes: G06Q 10/06398 Performance of employee with respect to a job function
• CPC Class Codes: G06Q 10/101 Collaborative creation, e.g. joint development of products or services
• CPC Class Codes: G06Q 10/103 Workflow collaboration or project management
• CPC Class Codes: G06V 2201/10 Recognition assisted with metadata

Abstract

Techniques are described for facilitating performance of tasks involving human review of media data (e.g., images, audio clips, video clips, etc.), such as to identify one or more targets of interest. The media data review may be performed for various reasons, such as to assist in locating one or more target objects in a large geographical area (e.g., one or more missing people or vehicles) based on human review of large quantities of images that each correspond to a small subset of the geographical area. When one or more of the reviewed media data pieces are identified as being relevant, information about those identified media data pieces may be used in various ways. Furthermore, in at least some situations, the media data review may be part of a charitable effort that uses human volunteers to review the media data without monetary payment or other compensation.

Claims

1. A computer-implemented method comprising:

obtaining, by one or more computing systems of a media target identifier system, information about a target identification effort to identify one or more indicated target objects in a plurality of images;

determining, by the one or more computing systems, an amount of memory to use on one or more client computing devices that will display at least one of the plurality of images;

generating, by the one or more computing systems, the plurality of images, including obtaining media data from one or more sources external to the media target identifier system about one or more areas of interest, and manipulating the media data to produce one or more indicated characteristics for each image of the plurality, wherein the one or more indicated characteristics includes a size of each image that is based at least in part on the determined amount of memory;

analyzing, by the one or more computing systems, at least some images of the plurality to prioritize one or more images of the plurality for the target identification effort; and

transmitting, by the one or more computing systems, the one or more images to the one or more client computing devices for display as part of identifying the one or more indicated target objects for the target identification effort.

2. The computer-implemented method of claim 1 wherein the analyzing of the at least some images includes determining a likelihood for each of the at least some images that the image includes at least one of the one or more indicated target objects.

3. The computer-implemented method of claim 1 wherein the one or more areas of interest are a geographical area, wherein the plurality of images in aggregate represent the geographical area such that each image of the plurality represents a subset of the geographical area, and wherein the analyzing of the at least some images includes determining that the at least some images represent a selected one of multiple portions of the geographical area.

4. The computer-implemented method of claim 1 wherein the manipulating of the media data to produce the one or more indicated characteristics for each image of the plurality includes modifying one or more of color, brightness, contrast, sharpness or noise in each image of the plurality.

5. The computer-implemented method of claim 1 wherein the manipulating of the media data to produce the one or more indicated characteristics for each image of the plurality further includes determining an image resolution, and producing each image of the plurality to have the determined image resolution.

6. The computer-implemented method of claim 1 further comprising determining, by the one or more computing systems and based at least in part on the analyzing, one or more additional images to acquire for further use in the target identification effort, and providing the one or more additional images to the one or more client computing devices.

7. The computer-implemented method of claim 1 further comprising coordinating performance, by the one or more computing systems, of further review of the prioritized one or more images for the target identification effort to determine whether the prioritized one or more images include the one or more indicated target objects, including obtaining results from the further review, and providing the received results.

8. The computer-implemented method of claim 1 wherein the media data include visual data of a geographical area, wherein the target identification effort is to identify one or more subsets of the geographical area in which the one or more indicated target objects are likely to be located, and wherein the one or more indicated target objects include at least one of a missing person or a missing vehicle.

9. A non-transitory computer-readable medium having stored contents that cause one or more computing systems to perform automated operations including at least:

obtaining, by the one or more computing systems, information about a target identification effort to identify one or more indicated target objects in a plurality of pieces of media;

generating, by the one or more computing systems, the plurality of pieces of media, including obtaining media data from one or more external sources about one or more areas of interest, and manipulating the media data to produce one or more indicated characteristics for each piece of media data of the plurality, wherein the one or more indicated characteristics includes a size of each piece of media data that is based on at least one of a determined amount of memory or a determined transmission rate;

analyzing, by the one or more computing systems, at least some pieces of media of the plurality to prioritize one or more pieces of media of the plurality for the target identification effort; and

providing, by the one or more computing systems, the one or more pieces of media for display on one or more client computing devices as part of identifying the one or more indicated target objects for the target identification effort.

10. The non-transitory computer-readable medium of claim 9 wherein the analyzing of the at least some pieces of media includes determining a likelihood for each of the at least some pieces of media that the piece of media data includes at least one of the one or more indicated target objects.

11. The non-transitory computer-readable medium of claim 9 wherein the one or more areas of interest are a geographical area, wherein the plurality of pieces of media in aggregate represent the geographical area such that each piece of media data of the plurality represents a subset of the geographical area, and wherein the analyzing of the at least some pieces of media includes determining that the at least some pieces of media represent a selected one of multiple portions of the geographical area.

12. The non-transitory computer-readable medium of claim 9 wherein the manipulating of the media data to produce the one or more indicated characteristics for each piece of media data of the plurality includes modifying one or more of color, brightness, contrast, sharpness or noise in each piece of media data of the plurality.

13. The non-transitory computer-readable medium of claim 9 wherein the plurality of pieces of media data include multiple images, and wherein the stored contents include instructions that, when executed, further cause the one or more computing systems to determine, based at least in part on the analyzing, one or more additional pieces of media to acquire for further use in the target identification effort, and to transmit the one or more additional pieces of media over one or more computer networks to the one or more client computing devices.

14. The non-transitory computer-readable medium of claim 9 wherein the stored contents include instructions that, when executed, further cause the one or more computing systems to coordinate performance of further review of the prioritized one or more pieces of media for the target identification effort to determine whether the prioritized one or more pieces of media include the one or more indicated target objects, including obtaining results from the further review and providing the received results, and wherein the one or more indicated target objects include at least one of a person or a vehicle missing in a geographical area that includes the one or more areas of interest.

15. A system comprising:

one or more hardware processors; and

one or more memories with stored instructions that, when executed by at least one of the one or more hardware processors, cause the system to perform automated operations that include at least;

obtaining information about a target identification effort to identify one or more indicated target objects in a plurality of images;

determining an amount of memory to use on one or more client computing devices that will display at least one of the plurality of images;

generating, using at least one of an amount of memory or a transmission rate, the plurality of images, including obtaining media data from one or more external sources about one or more areas of interest, and manipulating the media data to produce one or more indicated characteristics for each image of the plurality, wherein the one or more indicated characteristics includes a size of each image that is based at least in part on the determined amount of memory;

analyzing at least some images of the plurality to prioritize one or more images of the plurality for the target identification effort; and

providing, to the one or more client computing devices and over one or more computer networks, the one or more images for use in identifying the one or more indicated target objects for the target identification effort.

16. The system of claim 15 wherein the analyzing of the at least some images includes determining a likelihood for each of the at least some images that the image includes at least one of the one or more indicated target objects.

17. The system of claim 15 wherein the one or more areas of interest are a geographical area, wherein the plurality of images in aggregate represent the geographical area such that each image of the plurality represents a subset of the geographical area, and wherein the analyzing of the at least some images includes determining that the at least some images represent a selected one of multiple portions of the geographical area.

18. The system of claim 15 wherein the manipulating of the media data to produce the one or more indicated characteristics for each image of the plurality includes modifying one or more of color, brightness, contrast, sharpness or noise in each image of the plurality.

19. The system of claim 15 wherein the stored instructions further cause the system to determine, based at least in part on the analyzing, one or more additional pieces of media to acquire for further use in the target identification effort, and to transmit the one or more additional pieces of media to the one or more client computing devices.

20. The system of claim 15 wherein the stored instructions further cause the system to provide functionality of a media target identifier system, including coordinating performance of further review of the prioritized one or more images for the target identification effort to determine whether the prioritized one or more images include the one or more indicated target objects, including obtaining results from the further review and providing information related to the received results, and wherein the one or more indicated target objects include at least one of a person or a vehicle missing in a geographical area that includes the one or more areas of interest.