Open set recognition using transduction
First Claim
1. A pattern recognition system comprising:
- a) at least one capture device configured to acquire at least one sample, each of said at least one sample associated with a sample identifier;
b) a basis configured to encode at least one of said at least one sample, said basis derived using a multitude of representative training samples;
c) at least one feature extractor configured to generate at least one signature from at least one of said at least one sample using said basis;
d) a gallery, said gallery including at least one gallery sample, each of said at least one gallery sample being one of said at least one signature;
e) a rejection threshold, said rejection threshold created using a rejection threshold learning mechanism, said rejection threshold learning mechanism configured to calculate said rejection threshold using at least one of said at least one sample by;
i) swapping one of said sample identifier with other possible said sample identifier;
ii) computing a credibility value (p) for each of the swapped sample identifiers;
iii) deriving a peak-to-side ratio (PSR) distribution using a multitude of said credibility value; and
iv) determining said rejection threshold using said peak-to-side ratio distribution;
f) a storage mechanism configured to store at least one of said at least one gallery sample; and
g) an open set recognition stage configured to authenticate or reject as unknown the identity of at least one unknown sample, by;
i) deriving a set of credibility values by iteratively assign each of the gallery identifiers to the unknown sample and calculating a credibility value;
ii) deriving a peak-to-side ratio for said unknown sample using said set of credibility values;
iii) comparing said peak-to-side ratio for said unknown sample to said rejection threshold;
iv) rejecting said unknown sample as unknown if said peak-to-side ratio is less than or equal to said rejection threshold; and
v) finding the closest of said at least one gallery sample if said peak-to-side ratio is greater than said rejection threshold.
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Abstract
An open set recognition system utilizing transductive inference including capture device(s), a basis, quality checker(s), feature extractor(s), a gallery, a rejection threshold, a storage mechanism, and a recognition stage. The basis encodes sample(s) and is derived using training samples. The feature extractor(s) generates signature(s) from sample(s) using the basis. The rejection threshold is created using a rejection threshold learning mechanism that calculates the rejection threshold using sample(s) by: swapping a sample identifier with other sample identifier(s); computing a credibility value for the swapped sample identifiers; deriving a peak-to-side ratio distribution using the credibility values; and determining the rejection threshold using the peak-to-side ratio distribution. The open set recognition stage authenticates or reject as unknown the identity of unknown sample(s) using derived credibility values, derived peak-to-side ratios for the unknown sample and the rejection threshold.
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Citations
21 Claims
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1. A pattern recognition system comprising:
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a) at least one capture device configured to acquire at least one sample, each of said at least one sample associated with a sample identifier; b) a basis configured to encode at least one of said at least one sample, said basis derived using a multitude of representative training samples; c) at least one feature extractor configured to generate at least one signature from at least one of said at least one sample using said basis; d) a gallery, said gallery including at least one gallery sample, each of said at least one gallery sample being one of said at least one signature; e) a rejection threshold, said rejection threshold created using a rejection threshold learning mechanism, said rejection threshold learning mechanism configured to calculate said rejection threshold using at least one of said at least one sample by; i) swapping one of said sample identifier with other possible said sample identifier; ii) computing a credibility value (p) for each of the swapped sample identifiers; iii) deriving a peak-to-side ratio (PSR) distribution using a multitude of said credibility value; and iv) determining said rejection threshold using said peak-to-side ratio distribution; f) a storage mechanism configured to store at least one of said at least one gallery sample; and g) an open set recognition stage configured to authenticate or reject as unknown the identity of at least one unknown sample, by; i) deriving a set of credibility values by iteratively assign each of the gallery identifiers to the unknown sample and calculating a credibility value; ii) deriving a peak-to-side ratio for said unknown sample using said set of credibility values; iii) comparing said peak-to-side ratio for said unknown sample to said rejection threshold; iv) rejecting said unknown sample as unknown if said peak-to-side ratio is less than or equal to said rejection threshold; and v) finding the closest of said at least one gallery sample if said peak-to-side ratio is greater than said rejection threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A pattern recognition method comprising using a system to perform the steps of:
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a) acquiring at least one sample acquired from at least one capture device, each of said at least one sample associated with a sample identifier; b) encoding at least one of said at least one sample using a basis, said basis derived using a multitude of representative training samples; c)generating at least one signature from at least one of said at least one sample using said basis; d) storing at least one of said at least one signature in a gallery, each of said at least one signature being a gallery sample; e) calculating a rejection threshold using at least one of said at least one sample by; i) swapping one of said sample identifier with other possible said sample identifier; ii) computing a credibility value (p) for each of the swapped sample identifiers; iii) deriving a peak-to-side ratio (PSR) distribution using a multitude of said credibility value; and iv) determining said rejection threshold using said peak-to-side ratio distribution; and f) authenticating or rejecting as unknown the identity of at least one unknown sample, by; i) deriving a set of credibility values by iteratively assign each of the gallery identifiers to the unknown sample and calculating a credibility value; ii) deriving a peak-to-side ratio for said unknown sample using said set of credibility values; iii) comparing said peak-to-side ratio for said unknown sample to said rejection threshold; iv) rejecting said unknown sample as unknown if said peak-to-side ratio is less than or equal to said rejection threshold; and v) finding the closest of said at least one gallery sample if said peak-to-side ratio is greater than said rejection threshold. - View Dependent Claims (18, 19, 20, 21)
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Specification