Systems and methods for reducing data density in large datasets

• US 10,482,349 B2
• Filed: 12/05/2018
• Issued: 11/19/2019
• Est. Priority Date: 04/17/2015
• Status: Active Grant

• Current Assignee: Inscape Data, Inc. (VIZIO, Inc.)
• Original Assignee: Inscape Data, Inc. (VIZIO, Inc.)
• Inventors: Neumeier, Zeev
• Primary Examiner(s): Desire, Gregory M
• Application Number:
  US16/210,796
• Publication Number:
  US 20190188520A1
• Time in Patent Office: 349 Days
• CPC Class Codes: G06F 16/786 using motion, e.g. object motion or camera motion
• CPC Class Codes: G06F 18/2413 based on distances to training or reference patterns
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 20/40 in video content extracting overlay text G06V20/62; video retrieval G06F16/70; processing of video elementary streams in video servers H04N21/234; processing of video elementary streams in video clients H04N21/44
• CPC Class Codes: G06V 20/47 Detecting features for summarising video content
• CPC Class Codes: G06V 40/172 Classification, e.g. identification

Abstract

Techniques and systems are provided for identifying unknown content. For example, a number of vectors out of a plurality of vectors projected from an origin point can be determined that are between a reference data point and an unknown data point. The number of vectors can be used to estimate an angle between a first vector (from the origin point to a reference data point) and a second vector (from the origin point to an unknown data point). A distance between the reference data point and the unknown data point can then be determined. Using the determined distance, candidate data points can be determined from a set of reference data points. The candidate data points can be analyzed to identify the unknown data point.

Claims

1. A computer-implemented method, comprising:

obtaining a reference data point;

determining first representative data associated with the reference data point, the first representative data indicating a relationship between a vector associated with the reference data point and a plurality of projected vectors;

removing a number of bits associated with the reference data point from storage in response to determining the first representative data;

obtaining an unknown data point;

determining second representative data associated with the unknown data point, the second representative data indicating a relationship between a vector associated with the unknown data point and the plurality of projected vectors; and

identifying, using the first representative data and the second representative data, one or more candidate data points for matching the unknown data point, wherein identifying the one or more candidate data points includes comparing the unknown data point to the reference data point.

2. The method of claim 1, wherein the number of bits associated with the reference data point is removed prior to identifying one or more candidate data points for matching the unknown data point.

3. The method of claim 1, wherein the first representative data includes a length of the vector associated with the reference data point.

4. The method of claim 1, wherein the first representative data includes information indicating whether a projected vector is to an algebraic left or an algebraic right of the vector associated with the reference data point.

5. The method of claim 4, wherein the first representative data includes a length of the vector associated with the reference data point.

6. The method of claim 1, further comprising storing the first representative data.

7. The method of claim 1, wherein the second representative data includes a length of the vector associated with the unknown data point.

8. The method of claim 1, wherein the second representative data includes information indicating whether a projected vector is to an algebraic left or an algebraic right of the vector associated with the unknown data point.

9. The method of claim 8, wherein the second representative data includes a length of the vector associated with the unknown data point.

10. The method of claim 1, further comprising:

determining, using the first representative data and the second representative data, third representative data, the third representative data indicating a relationship between the vector associated with the reference data point and the vector associated with the unknown data point; and

identifying the reference data point as a candidate data point based on the third representative data.

11. The method of claim 10, wherein the third representative data includes an angle between the vector associated with the reference data point and the vector associated with the unknown data point.

12. The method of claim 10, wherein the third representative data includes an angle between the vector associated with the reference data point and the vector associated with the unknown data point, and wherein the angle is estimated based on a number of the plurality of projected vectors between the vector associated with the reference data point and the vector associated with the unknown data point.

13. The method of claim 10, wherein the third representative data includes a distance between the reference data point and the unknown data point.

14. The method of claim 10, wherein the third representative data includes:

an angle between the vector associated with the reference data point and the vector associated with the unknown data point; and

a distance between the reference data point and the unknown data point, wherein the distance is determined using the angle, a length of the vector associated with the reference data point, and a length of the vector associated with the unknown data point, and wherein the reference data point is identified as the candidate data point based on the distance.

15. The method of claim 1, wherein the unknown data point is associated with content being presented by a display.

16. The method of claim 1, further comprising identifying video content being presented by a display, wherein identifying the video content includes comparing the unknown data point with the one or more candidate data points.

17. The method of claim 1, wherein the reference data point includes pixel data, and wherein removing the number of bits associated with the reference data point includes removing some or all of the pixel data from the storage.

18. A system comprising:

one or more processors;

one or more non-transitory machine-readable storage media containing instructions which when executed on the one or more processors, cause the one or more processors to perform operations including;

obtaining a reference data point;

determining first representative data associated with the reference data point, the first representative data indicating a relationship between a vector associated with the reference data point and a plurality of projected vectors;

removing a number of bits associated with the reference data point from storage in response to determining the first representative data;

obtaining an unknown data point;

determining second representative data associated with the unknown data point, the second representative data indicating a relationship between a vector associated with the unknown data point and the plurality of projected vectors; and

identifying, using the first representative data and the second representative data, one or more candidate data points for matching the unknown data point, wherein identifying the one or more candidate data points includes comparing the unknown data point to the reference data point.

19. The system of claim 18, wherein the number of bits associated with the reference data point is removed prior to identifying one or more candidate data points for matching the unknown data point.

20. The system of claim 18, further comprising instructions, which when executed on the one or more processors, cause the one or more processors to perform operations including:

determining, using the first representative data and the second representative data, third representative data, the third representative data indicating a relationship between the vector associated with the reference data point and the vector associated with the unknown data point; and

identifying the reference data point as a candidate data point based on the third representative data.