Digital goods representation based upon matrix invariants using non-negative matrix factorizations

• US 20070076869A1
• Filed: 10/03/2005
• Published: 04/05/2007
• Est. Priority Date: 10/03/2005
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Monga, Vishal, Mihcak, Mehmet
• Application Number:
  US11/242,632
• Publication Number:
  US 20070076869A1
• Time in Patent Office: Days
• US Class Current: 380/54
• CPC Class Codes: G06F 2221/2111 Location-sensitive, e.g. geographical location, GPS
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions

Abstract

Described herein is one or more implementations that produce a new representation of a digital good (such as an image) in a new defined representation domain. In particular, the representations in this new domain are based upon matrix invariants. More particularly still, the specific matrix invariants described herein include non-negative matrix factorizations (NMF).

Claims

1. A processor-readable medium having processor-executable instructions that, when executed by a processor, performs a method comprised of representing digital goods in a defined representation domain, wherein such representation is based upon matrix invariants, wherein the matrix invariants include non-negative matrix factorizations (NMF).

2. A medium as recited in claim 1, wherein the method further comprises extracting robust pseudo-random features of the digital goods, wherein the features are within the defined representation domain.

3. A medium as recited in claim 1, wherein the digital goods is selected from a group consisting of a digital image, a digital audio clip, a digital video, a database, and a software image.

4. A computing device comprising:

an audio/visual output;

a medium as recited in claim 1.

5. A processor-readable medium having processor-executable instructions that, when executed by a processor, performs a method facilitating protection of digital goods, the method comprising:

obtaining a digital good;

partitioning the good into a plurality of regions;

calculating statistics of one or more of the regions of the plurality, so that the statistics of a region are representative of it, wherein the statistics calculated are based upon matrix invariants, wherein the matrix invariants include non-negative matrix factorizations (NMF).

6. A medium as recited in claim 5, wherein at least some of the plurality of regions overlap.

7. A medium as recited in claim 5, wherein the partitioning comprises pseudo-randomly segmenting the good into a plurality of regions.

8. A medium as recited in claim 5, wherein the digital goods is selected from a group consisting of a digital image, a digital audio clip, a digital video, a database, and a software image.

9. A medium as recited in claim 5, wherein the method further comprises producing output comprising the calculated statistics of one or more regions.

10. A modulated signal generated by a medium as recited in claim 9.

11. A computer comprising one or more processor-readable media as recited in claim 5.

12. A method comprising:

obtaining a digital good;

partitioning the good into a plurality of regions;

extracting robust features from the plurality of regions, wherein the features are based upon matrix invariant non-negative matrix factorizations (NMF).

13. A method as recited in claim 12, wherein the extracting act is characterized by calculating statistics of one or more of the regions of the plurality, so that the statistics of a region are representative of it, wherein the statistics calculated are based upon the matrix invariant NMF.

14. A method as recited in claim 12, wherein at least some of the plurality of regions overlap.

15. A method as recited in claim 12, wherein the partitioning comprises pseudo-randomly segmenting the good into a plurality of regions.

16. A method as recited in claim 12, wherein the digital goods is selected from a group consisting of a digital image, a digital audio clip, a digital video, a database, and a software image.

17. A method as recited in claim 12, wherein the method further comprises producing output comprising the robust features of one or more regions.