PATENT CLAIM ANALYSIS

Application Number: 15934521
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-06
Patent Classification: ["345", "423000"]

Abstract:
A three-dimensional model (e.g., motion capture model) of a user is generated from captured images or captured video of the user. A machine learning network may track poses and expressions of the user to generate and refine the three-dimensional model. Refinement of the three-dimensional model may provide more accurate tracking of the user's face. Refining of the three-dimensional model may include refining the determinations of poses and expressions at defined locations (e.g., eye corners and/or nose) in the three-dimensional model. The refining may occur in an iterative process. Tracking of the three-dimensional model over time (e.g., during video capture) may be used to generate an animated three-dimensional model (e.g., an animated puppet) of the user that simulates the user's poses and expressions.

Claim (Index 1):
A method, comprising:\n obtaining at least one image of a face of a user using a camera located on a device, the device comprising a computer processor, a memory, and a display; encoding, using the computer processor, the at least one image to generate one or more first feature vectors, wherein the first feature vectors represent one or more facial features of the user in the at least one image; determining, using the computer processor, a pose of the face of the user and one or more muscle activations of the face of the user from the first feature vectors; generating, using the computer processor, a three-dimensional model of the user's face based on the determined pose and muscle activations for the user's face; projecting, using the computer processor, the three-dimensional model onto the at least one image; defining, using the computer processor, one or more selected locations on the three-dimensional model; using the three-dimensional model projected onto the at least one image, encoding, at least once, using the computer processor, the at least one image at the selected locations to generate one or more second feature vectors for the at least one image, wherein the second feature vectors represent one or more facial features of the user at the selected locations in the at least one image; refining, at least once, using the computer processor, the determination of the pose of the face of the user and the one or more muscle activations of the face of the user using the second feature vectors; and refining, at least once, using the computer processor, the generated three-dimensional model of the user's face based on the refined pose and muscle activations for the user's face.

Metadata:
- Claim Count in Document: 42.0
- Percentile: 90.0
- Lexical Diversity: 2.15152
- Patent Class: 345.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['10444278', '13711639', '13168389', '12811237', '14882624']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6223674363237156
- 35 USC 102 Novelty (BERT): 0.4710264658459754
- Combined Prediction Score: 0.6072333392759416
- Mean Citation Score: 159.433628
- Max Citation Score: 178.63208
- Similarity Product: 137.56698130255222

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