Content recognizer via probabilistic mirror distribution
First Claim
1. A computer-readable medium having computer-executable instructions that, when executed by a computer, performs a method facilitating the recognition of content of digital goods, the method comprising:
- obtaining a digital good;
segmenting the good into a plurality of regions;
for each region of the plurality;
defining one or more sub-regions inside of a region ;
computing suitable statistics for sub-region ;
quantizing the statistics for region ;
generating weighting factor mij for one or more points xij of region ;
producing a quantization qR of region based upon one or more weighting factors mij of one or more points xij;
producing a recognition indication based upon a combination of the quantizations qR of the regions of the plurality.
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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.
34 Citations
34 Claims
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1. A computer-readable medium having computer-executable instructions that, when executed by a computer, performs 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 regions; for each region of the plurality; defining one or more sub-regions inside of a region ; computing suitable statistics for sub-region ; quantizing the statistics for region ; generating weighting factor mij for one or more points xij of region ; producing a quantization qR of region based upon one or more weighting factors mij of one or more points xij; producing a recognition indication based upon a combination of the quantizations qR of the regions of the plurality. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computer-readable medium having computer-executable instructions that, when executed by a computer, performs 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 regions; for each region of the plurality; generating weighting factor mij for one or more points xij of a region; producing a quantization qR of a region based upon one or more weighting factors mij of one or more points xij; producing a recognition indication based on the quantizations qR of the regions of the plurality. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. 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 regions; for each region of the plurality; generating weighting factor mij for one or more points xij of a region; producing a quantization qR of a region based upon one or more weighting factors mij of one or more points xij; producing a recognition indication based on the quantizations qR of the regions of the plurality. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29, 30, 31)
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32. A system comprising:
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a segmenter configured to generate multiple, pseudorandomly sized and distributed plurality of regions; a weighting-factor generator configured to generate a weighting factor mij for one or more points xij of one or more regions of the plurality; a region quantizer configured to produce a quantization qR of a region based upon one or more weighting factors mij of one or more points xij of one or more regions of the plurality; a combiner configured to produce a recognition indication based on the quantizations qR of the regions of the plurality. - View Dependent Claims (33, 34)
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Specification