Efficient classification of three dimensional face models for human identification and other applications
First Claim
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1. A method comprising obtaining a plurality of reference faces;
- obtaining a plurality of enrollment faces, representing faces about which information is already known;
comparing at least a plurality of said enrollment faces with said reference faces to produce a plurality of enrollment scores representing differences between each of the plurality of enrollment faces and said reference faces;
obtaining a query face, and comparing said query face with said reference faces to produce a plurality of query scores representing differences between said query face and said reference faces; and
comparing said query scores with said plurality of enrollment scores to determine matches between said query face and said plurality of enrollment faces.
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Abstract
Three dimensional face recognition via vectorizing samples that are in an enrollment data base. The vectors are formed by comparing faces in the enrollment database with reference faces, and determining differences between the actual faces and the reference faces. Those differences are then formed into an N dimensional vector representing the classified faces. A query face is then similarly vectorized and compared to precomputed vectors indicative of the faces in the database. Another technique is described for updating the reference faces based on an error level.
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Citations
27 Claims
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1. A method comprising
obtaining a plurality of reference faces; -
obtaining a plurality of enrollment faces, representing faces about which information is already known;
comparing at least a plurality of said enrollment faces with said reference faces to produce a plurality of enrollment scores representing differences between each of the plurality of enrollment faces and said reference faces;
obtaining a query face, and comparing said query face with said reference faces to produce a plurality of query scores representing differences between said query face and said reference faces; and
comparing said query scores with said plurality of enrollment scores to determine matches between said query face and said plurality of enrollment faces. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method comprising:
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converting a plurality of three-dimensional enrollment models into N-dimensional enrollment model vectors, by comparing the plurality of enrollment models to reference models, obtaining differences between each of the plurality of enrollment models and each of the reference models, and using said differences to form said N dimensional enrollment model vectors;
converting a query model, representing a face to be recognized, into an n dimensional query model vector, by comparing the query model to said reference models, obtaining the differences between the query model and the reference models, and using said differences to form an N dimensional query vector;
comparing the query vector to said enrollment model vectors and producing information indicative of matches therebetween. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
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23. A system comprising
a database, storing information about a plurality of enrollment faces, representing faces about which information is already known, and storing a plurality of enrollment vectors, representing differences between each of the plurality of enrollment faces and a plurality of reference faces; a query station, that obtains a query face, compares said query face with said reference faces to produce a query vector representing differences between said query face and said reference faces, and compares said query vector with said plurality of enrollment vectors to determine matches between said query face and said plurality of enrollment faces, and produces information indicative of said matches. - View Dependent Claims (24, 25, 26, 27)
Specification