PATENT CLAIM ANALYSIS

Application Number: 16207475
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-04
Patent Classification: ["382", "118000"]

Abstract:
A method for facial recognition encode analysis comprises providing a training set of Gabor encoded arrays of face images from a database; and, for each encode array in the training set, evaluating the Gabor data to determine the accuracy of the fiducial points on which the encode array is based. The method also comprises training an outlier detection algorithm based on the evaluation of the encode arrays to obtain a decision function for a strength of accuracy of fiducial points in the encode arrays; and outputting the decision function for application to an encode array to be tested.

Claim (Index 18):
The computer program product of  claim 15 , wherein the determined accuracy of the fiducial points is based on an evaluation of each encode array in the training set of Gabor encoded arrays by determining a set of correlations between Gabor wavelets of different frequencies at pairs of sampling locations related through facial symmetry or spatial overlap.

Metadata:
- Claim Count in Document: 43.0
- Percentile: 98.0
- Lexical Diversity: 1.92593
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15192091', '15703082', '14324991', '13488415', '14530585']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3628442258333086
- 35 USC 102 Novelty (BERT): 0.5198728638010128
- Combined Prediction Score: 0.3785470896300791
- Mean Citation Score: 213.260984
- Max Citation Score: 331.40674
- Similarity Product: 299.33082459543823

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test