PATENT CLAIM ANALYSIS

Application Number: 15985173
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-09
Patent Classification: ["345", "646000"]

Abstract:
A method for automatic facial impression transformation includes extracting landmark points for elements of a target face whose facial impression is to be transformed as well as distance vectors respectively representing distances of the landmark points, comparing the distance vectors to select a learning data set similar to the target face from a database, extracting landmark points and distance vectors from the learning data set, transforming a local feature of the target face based on the landmark points of the learning data set and score data for a facial impression, and transforming a global feature of the target face based on the distance vectors of the learning data set and the score data for the facial impression. Accordingly, a facial impression may be transformed in various ways while keeping an identity of a corresponding person.

Claim (Index 4):
The method of  claim 1 , wherein the transforming of the facial impression of the target face comprises:\n generating a target function based on the distance vectors of the learning data set and score data of a facial impression; and determining locations and angles of the elements of the target face by moving landmark points associated with the second distance vector, based on the target function.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 93.0
- Lexical Diversity: 2.44828
- Patent Class: 345.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15069095', '14863772', '14131374', '12079276', '14561757']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6742556912287622
- 35 USC 102 Novelty (BERT): 0.5840438159815639
- Combined Prediction Score: 0.6652345037040424
- Mean Citation Score: 282.859016
- Max Citation Score: 491.3998
- Similarity Product: 435.8411146718383

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test