Building systems for adaptive tracking of facial features across individuals and groups
First Claim
1. A computer implemented method for generating a non-transient record embodying measures of an adaptive set of feature locations characterizing a face of a person, the method comprising:
- a. receiving a video sequence that constitutes a physical record of the face of a specified individual person;
b. applying a feature locator update model to the video sequence, the feature locator update model derived by steps of;
i. defining a set of training data consisting of training images with associated facial feature locations;
ii. generating a set of facial feature displacements for each training image with associated image sample vectors; and
iii. training a regularized linear regression which maps from image sample vectors to displacement vectors, wherein the regularized linear regression is characterized by regularization that includes a spatial smoothness term within the shape-free sample space;
c. extracting a plurality of locations corresponding to the adaptive set of feature locations;
d. based on the feature locator update model, characterizing the locations of features of the face of the specified individual person; and
e. storing the locations of features to the non-transient record.
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Abstract
Computer implemented methods for generating a non-transient record of feature locations and/or facial expression parameters characterizing a person'"'"'s face. A video sequence of a specified individual person is received and a feature locator update model is applied to the video sequence. The feature locator update model is derived by defining a set of training images, generating a set of facial feature displacements for each training image with associated image sample vectors, and training a regularized linear regression which maps from image sample vectors to displacement vectors, wherein the regularization includes a spatial smoothness term within the shape-free sample space. A feature location and/or a facial expression parameter is then extracted, based on the feature update model, characterizing the location, and/or the expression, of a selected set of features of the face of the specified individual person that correspond to an adaptive set of feature locations.
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Citations
22 Claims
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1. A computer implemented method for generating a non-transient record embodying measures of an adaptive set of feature locations characterizing a face of a person, the method comprising:
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a. receiving a video sequence that constitutes a physical record of the face of a specified individual person; b. applying a feature locator update model to the video sequence, the feature locator update model derived by steps of; i. defining a set of training data consisting of training images with associated facial feature locations; ii. generating a set of facial feature displacements for each training image with associated image sample vectors; and iii. training a regularized linear regression which maps from image sample vectors to displacement vectors, wherein the regularized linear regression is characterized by regularization that includes a spatial smoothness term within the shape-free sample space; c. extracting a plurality of locations corresponding to the adaptive set of feature locations; d. based on the feature locator update model, characterizing the locations of features of the face of the specified individual person; and e. storing the locations of features to the non-transient record. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A non-transitory computer readable medium for use on a computer system for storing computer-readable program code, the computer readable program code comprising:
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a. a computer code module for receiving a video sequence that constitutes a physical record of the face of a specified individual person; b. a computer code module for applying a feature locator update model to the video sequence; c. a computer code module for defining a set of training data consisting of training images with associated facial feature locations; d. a computer code module for generating a set of facial feature displacements for each training image with associated image sample vectors; e. a computer code module for training a regularized linear regression which maps from image sample vectors to displacement vectors, wherein the regularized linear regression is characterized by regularization that includes a spatial smoothness term within the shape-free sample space, thereby generating the feature locator update model; f. a computer code module for extracting a plurality of feature locations corresponding to an adaptive set of feature locations; g. a computer code module characterizing the plurality of feature locations of the face of the specified individual person based on the feature update model; and h. a computer code module for storing the plurality of feature locations to a non-transient medium. - View Dependent Claims (22)
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Specification