Automatic biometric identification based on face recognition and support vector machines
AssigneeTelecom Italia S.p.A.
InventorsMadalina Baltatu, Rosalia D'Alessandro, Roberta D'Amico, Massimo Tistarelli, Enrico Grosso, Manuele Bicego
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Abstract
An automatic biometric identification method based on face recognition and support vector machines, includes enrolling a user to generate a user's reference template; and identifying the user based on the user's reference template, wherein generating a user's reference template includes acquiring a number of user's face images, and training a one-class support vector machine based on the user's face images only.
Claims24
An automatic biometric identification method based on face recognition and support vector machines, comprises:
- generating a user's reference template;
- and
- identifying the user based on the user's reference template;
- wherein
- generating the user's reference template comprises:
- acquiring a number of user's face images;
- and
- training a support vector machine based on the user's face images;
- the support vector machine being a one-class support vector machine trained based on user's face images only, wherein training the one-class support vector machine comprises:
- extracting a feature vector from each user's face image;
- and
- training the one-class support vector machine based on the extracted feature vectors, wherein
- extracting the feature vector from each user's face image comprises:
- computing a transform in the frequency domain of each user's face image to generate a respective spectrum;
- and
- forming the feature vector for each user's face image based on coefficients of frequencies of the respective spectrum which comprise coefficients of low frequencies of the respective spectrum.
An automatic biometric identification method based on face recognition and one class support vector machines, comprises:
- generating a user's reference template;
- and
- identifying the user based on the user's reference template;
- wherein
- generating the user's reference template comprises:
- acquiring a number of user's face images;
- and
- training a number of one-class support vector machines equal to the number of regions in the user's face images, each one-class support vector machine being trained based on the feature vectors extracted from a corresponding region in the user's face images;
- the one-class support vector machines trained based on user's face images only, wherein
- training the one-class support vector machines comprises:
- extracting a feature vector from each user's face image;
- and
- training the one-class support vector machines based on the extracted feature vectors and wherein
- extracting the feature vector from each user's face image comprises:
- dividing each user's face image into a number of regions;
- and
- extracting the feature vector from at least some regions in the user's face image.
An automatic biometric identification system based on face recognition and support vector machines, comprising:
- a module for generating a user's reference template, the module comprising a support vector machine;
- a module for identifying the user based on the user's reference template;
- wherein
- said module for generating the user's reference template comprises:
- a module for acquiring a number of user's face images;
- and
- a module for training the support vector machine based on the user's face images;
- the support vector machine being a one-class support vector machine trained based on user's face images only, wherein training the one-class support vector machine comprises:
- extracting a feature vector from each user's face image;
- and
- training the one-class support vector machine based on the extracted feature vectors, wherein
- extracting the feature vector from each user's face image comprises:
- computing a transform in the frequency domain of each user's face image to generate a respective spectrum;
- and
- forming the feature vector for each user's face image based on coefficients of frequencies of the respective spectrum which comprise coefficients of low frequencies of the respective spectrum.
An automatic biometric identification system based on face recognition and support vector machines, comprising:
- a module for generating a user's reference template, the module comprising a support vector machine;
- a module for identifying the user based on the user's reference template;
- wherein
- said module for generating the user's reference template comprises:
- a module for acquiring a number of user's face images;
- and
- a module for training a number of one-class support vector machines equal to the number of regions in the user's face images;
- the support vector machines being a one-class support vector machine trained based on user's face images only, wherein
- training the one-class support vector machines comprises:
- extracting a feature vector from each user's face image;
- and
- training the one-class support vector machines based on the extracted feature vectors and wherein
- extracting the feature vector from each user's face image comprises:
- dividing each user's face image into a number of regions;
- and
- extracting the feature vector from at least some regions in the user's face image.
Dependencies are inferred from the claim text.