Content recognizer via probabilistic mirror distribution
First Claim
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1. A method comprising:
- obtaining a digital good;
segmenting the good into a plurality of regions; and
producing a recognition indication for the digital good based upon a combination of quantizations qR for each region of the plurality,further comprising, prior to said producing a recognition indication, generating weighting factor mij for one or more points xij of each region of the plurality of regions, wherein the generating comprises;
defining one or more sub-regions Sij inside of a region R;
computing suitable statistics for sub-region Sij;
quantizing the statistics for region R; and
generating weighting factor mij for one or more points xij of region R.
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Abstract
An implementation of a technology, described herein, for facilitating the recognition of content of digital goods. At least one implementation, described herein, derives a probabilistic mirror distribution of a digital good (e.g., digital image or audio signal). It uses the resulting data to derive weighting factors (i.e., coefficients) for the digital good. Based, at least in part on such weighting factors, it determines statistics of the good and quantizes it. The scope of the present invention is pointed out in the appending claims.
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11 Claims
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1. A method comprising:
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obtaining a digital good; segmenting the good into a plurality of regions; and producing a recognition indication for the digital good based upon a combination of quantizations qR for each region of the plurality, further comprising, prior to said producing a recognition indication, generating weighting factor mij for one or more points xij of each region of the plurality of regions, wherein the generating comprises; defining one or more sub-regions Sij inside of a region R; computing suitable statistics for sub-region Sij; quantizing the statistics for region R; and generating weighting factor mij for one or more points xij of region R. - View Dependent Claims (2, 3, 4, 5)
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6. A method facilitating the recognition of content of digital goods, the method comprising:
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obtaining a digital good; segmenting the good into a plurality of pseudorandomly sized and pseudorandomly distributed regions; and producing a recognition indication for the digital good, further comprising, prior to said producing a recognition indication, generating weighting factor mij for one or more points xij of each region of the plurality of distributed regions, wherein the generating comprises; defining one or more sub-regions Sij inside of a region R; computing suitable statistics for sub-region Sij; quantizing the statistics for region R; and generating weighting factor mij for one or more points xij of region R. - View Dependent Claims (7, 8, 9, 10, 11)
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Specification