FACE RECOGNITION IN BIG DATA ECOSYSTEM USING MULTIPLE RECOGNITION MODELS
First Claim
1. A computer-implemented method of training a facial recognition modeling system using an extremely large data set of facial images, the method comprising:
- distributing a plurality of facial recognition models across a plurality of nodes within the facial recognition modeling system; and
optimizing a facial matching accuracy of the facial recognition modeling system by increasing a facial image set variance among the plurality of facial recognition models, wherein, to optimize the facial matching accuracy of the facial recognition modeling system, the program code when executed is further operable to;
match each facial image of the data set of facial images with at least one of the facial recognition models; and
insert a facial image of the data set of facial images into a facial recognition model of the plurality of facial recognition models, wherein the facial recognition model is associated with a least closely matching facial image.
1 Assignment
0 Petitions
Accused Products
Abstract
A system trains a facial recognition modeling system using an extremely large data set of facial images, by distributing a plurality of facial recognition models across a plurality of nodes within the facial recognition modeling system. The system optimizes a facial matching accuracy of the facial recognition modeling system by increasing a facial image set variance among the plurality of facial recognition models. The system selectively matches each facial image within the extremely large data set of facial images with at least one of the plurality of facial recognition models. The system reduces the time associated with training the facial recognition modeling system by load balancing the extremely large data set of facial images across the plurality of facial recognition models while improving the facial matching accuracy associated with each of the plurality of facial recognition models.
-
Citations
10 Claims
-
1. A computer-implemented method of training a facial recognition modeling system using an extremely large data set of facial images, the method comprising:
-
distributing a plurality of facial recognition models across a plurality of nodes within the facial recognition modeling system; and optimizing a facial matching accuracy of the facial recognition modeling system by increasing a facial image set variance among the plurality of facial recognition models, wherein, to optimize the facial matching accuracy of the facial recognition modeling system, the program code when executed is further operable to; match each facial image of the data set of facial images with at least one of the facial recognition models; and insert a facial image of the data set of facial images into a facial recognition model of the plurality of facial recognition models, wherein the facial recognition model is associated with a least closely matching facial image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
-
Specification