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 5):
The non-transitory computer readable medium of  claim 4 , further comprising instructions that, when executed by the at least one processor, cause the computing device to:\n input subsequent joint features for the joints of the initial skeleton and the encoded feature vector for the initial joint features into the motion synthesis neural network, wherein the subsequent joint features correspond to a subsequent time of the motion sequence; utilize the encoder recurrent neural network and the decoder recurrent neural network to generate subsequent predicted joint rotations for the joints of the target skeleton based on the subsequent joint features and the encoded feature vector for the initial joint features; and utilize the forward kinematics layer to generate subsequent predicted joint features for joints of the target skeleton for the subsequent time of the motion sequence based on the subsequent predicted joint rotations, wherein the subsequent predicted joint features for joints of the target skeleton reflect the subsequent joint features for the joints of the 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): 0.6021625952074703
- 35 USC 102 Novelty (BERT): 0.5046597134448125
- Combined Prediction Score: 0.5924123070312045
- Mean Citation Score: 221.958358
- Max Citation Score: 235.20923
- Similarity Product: 160.91778728732288

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