PATENT CLAIM ANALYSIS

Application Number: 15926787
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["345", "474000"]

Abstract:
This disclosure relates to methods, non-transitory computer readable media, and systems that use a motion synthesis neural network with a forward kinematics layer to generate a motion sequence for a target skeleton based on an initial motion sequence for an initial skeleton. In certain embodiments, the methods, non-transitory computer readable media, and systems use a motion synthesis neural network comprising an encoder recurrent neural network, a decoder recurrent neural network, and a forward kinematics layer to retarget motion sequences. To train the motion synthesis neural network to retarget such motion sequences, in some implementations, the disclosed methods, non-transitory computer readable media, and systems modify parameters of the motion synthesis neural network based on one or both of an adversarial loss and a cycle consistency loss.

Claim (Index 13):
The system of  claim 9 , further comprising instructions that, when executed by the at least one processor, cause the system to train the motion synthesis neural network by:\n providing the predicted joint features of the training target skeleton to the motion synthesis neural network, wherein the predicted joint features correspond to the initial time of the training target motion sequence; utilizing the motion synthesis neural network to generate consistency joint features for the joints of the training initial skeleton for the initial time of the training motion sequence; and determining a cycle consistency loss by comparing the consistency joint features for the joints of the training initial skeleton with the training input joint features for the joints of the training initial skeleton.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 90.0
- Lexical Diversity: 2.31667
- Patent Class: 345.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15807028', '15174863', '15224519', '15147222', '15872408']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6002787222115877
- 35 USC 102 Novelty (BERT): 0.513122832134821
- Combined Prediction Score: 0.5915631332039111
- Mean Citation Score: 221.958358
- Max Citation Score: 235.20923
- Similarity Product: 142.1682625959146

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