System and method for determining the characteristics of human personality and providing real-time recommendations
First Claim
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1. A system for identifying a personality of a human subject comprising:
- one or more hardware processors; and
a computer-readable medium storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising;
receiving visual data of the human subject from one or more hardware sensors;
validating the visual data using a facial recognition algorithm, wherein the validation of the visual data comprises;
after determining that the visual data comprises an image of a distorted anatomical feature, correcting the distorted anatomical feature in the visual data;
detecting at least one anatomical feature of the human subject from the validated visual data, wherein detecting the at least one anatomical feature of the human subject comprises;
locating a physical region corresponding to each of the at least one anatomical feature in the validated visual data,extracting a geometrical representation of each of the at least one anatomical feature from the physical region, andassociating a first personality factor with each of the at least one anatomical feature, wherein the first personality factor is determined based on the geometrical representation of the anatomical feature; and
determining the personality of the human subject based on the first personality factor associated with each of the detected at least one anatomical feature using a hidden Markov model algorithm, and a plurality of hidden Markov models each of which corresponding to a plurality of personalities by;
determining a hidden Markov model from the plurality of hidden Markov models that maximizes a probability of observing a sequence of first personality factors associated with the detected anatomical features, anddetermining the personality from a plurality of personalities corresponding to the determined hidden Markov model by determining a centroid of a N-dimension region corresponding to the plurality of personalities corresponding to the determined hidden Markov model.
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Abstract
The present disclosure relates to systems, methods, and non-transitory computer-readable media for identifying a personality of a human subject based on correlations between personality traits obtained from the subject'"'"'s physical features, which may include a movement pattern of the subject, such as the subject'"'"'s gait. Embodiments in accordance with the present disclosure are further capable of providing a recommendation to the subject for a product or service based on the identified personality of the subject.
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Citations
27 Claims
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1. A system for identifying a personality of a human subject comprising:
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one or more hardware processors; and a computer-readable medium storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising; receiving visual data of the human subject from one or more hardware sensors; validating the visual data using a facial recognition algorithm, wherein the validation of the visual data comprises;
after determining that the visual data comprises an image of a distorted anatomical feature, correcting the distorted anatomical feature in the visual data;detecting at least one anatomical feature of the human subject from the validated visual data, wherein detecting the at least one anatomical feature of the human subject comprises; locating a physical region corresponding to each of the at least one anatomical feature in the validated visual data, extracting a geometrical representation of each of the at least one anatomical feature from the physical region, and associating a first personality factor with each of the at least one anatomical feature, wherein the first personality factor is determined based on the geometrical representation of the anatomical feature; and determining the personality of the human subject based on the first personality factor associated with each of the detected at least one anatomical feature using a hidden Markov model algorithm, and a plurality of hidden Markov models each of which corresponding to a plurality of personalities by; determining a hidden Markov model from the plurality of hidden Markov models that maximizes a probability of observing a sequence of first personality factors associated with the detected anatomical features, and determining the personality from a plurality of personalities corresponding to the determined hidden Markov model by determining a centroid of a N-dimension region corresponding to the plurality of personalities corresponding to the determined hidden Markov model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A non-transitory computer-readable medium storing instructions for identifying a personality of a human subject that, when executed by one or more hardware processors, cause the one or more hardware processors to perform operations comprising:
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receiving visual data of the human subject from one or more hardware sensors; validating the visual data using a facial recognition algorithm, wherein the validation of the visual data comprises;
after determining that the visual data comprises an image of a distorted anatomical feature, correcting the distorted anatomical feature in the visual data;detecting at least one anatomical feature of the human subject from the validated visual data, wherein detecting the at least one anatomical feature of the human subject comprises; locating a physical region corresponding to each of the at least one anatomical feature in the validated visual data, extracting a geometrical representation of each of the at least one anatomical feature from the physical region, and associating a first personality factor with each of the at least one anatomical feature, wherein the first personality factor is determined using the geometrical representation of the anatomical feature; and determining the personality of the human subject based on the first personality factor associated with each of the detected at least one anatomical feature using a hidden Markov model algorithm, and a plurality of hidden Markov models each of which corresponding to a plurality of personalities by; determining a hidden Markov model from the plurality of hidden Markov models that maximizes a probability of observing a sequence of first personality factors associated with the detected anatomical features, and determining the personality from a plurality of personalities corresponding to the determined hidden Markov model by determining a centroid of a N-dimension region corresponding to the plurality of personalities corresponding to the determined hidden Markov model. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19)
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20. A method for identifying a personality of a human subject comprising:
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receiving, using one or more hardware processors, visual data of the human subject from one or more hardware sensors; validating, using one or more hardware processors, the visual data using a facial recognition algorithm, wherein the validation of the visual data comprises;
after determining that the visual data comprises an image of a distorted anatomical feature, correcting the distorted anatomical feature in the visual data;detecting, using one or more hardware processors, at least one anatomical feature of the human subject from the validated visual data, wherein detecting the at least one anatomical feature of the human subject comprises; locating a physical region corresponding to each of the at least one anatomical feature in the validated visual data, extracting a geometrical representation of each of the at least one anatomical feature from the physical region, and associating a first personality factor with each of the at least one anatomical feature, wherein the first personality factor is determined using the geometrical representation of the anatomical feature; and determining, using one or more hardware processors, the personality of the human subject based on the first personality factor associated with each of the detected at least one anatomical feature using a hidden Markov model algorithm, and a plurality of hidden Markov models each of which corresponding to a plurality of personalities by; determining a hidden Markov model from the plurality of hidden Markov models that maximizes a probability of observing a sequence of first personality factors associated with the detected anatomical features, and determining the personality from a plurality of personalities corresponding to the determined hidden Markov model by determining a centroid of a N-dimension region corresponding to the plurality of personalities corresponding to the determined hidden Markov model. - View Dependent Claims (21, 22, 23, 24, 25, 26, 27)
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Specification