PATENT CLAIM ANALYSIS

Application Number: 16137782
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-03
Patent Classification: ["348", "143000"]

Abstract:
A system and method for implementing a machine learning-based system for generating event intelligence from video image data that: collects input of the live video image data; detects coarse features within the live video image data; constructs a coarse feature mapping comprising a mapping of the one or more coarse features; receives input of the coarse feature mapping at each of a plurality of distinct sub-models; identify objects within the live video image data based on the coarse feature mapping; identify one or more activities associated with the objects within the live video image data; identify one or more interactions between at least two of the objects within the live video image data based at least on the one or more activities; composes natural language descriptions based on the one or more activities associated with the objects and the one or more interactions between the objects; and constructs an intelligence augmented live video image data.

Claim (Index 17):
The method according to  claim 16 , further comprising:\n implementing a mutual feature data exploration engine that:\n collects feature output data generated by each of the plurality of distinct sub-models of the ensemble, wherein the feature output data includes extracted features from the video image data output from each of the plurality of distinct sub-models; \n identifies and extracts mutuality data and/or relationship data between one or more pairs of extracted features, wherein each of the one or more pairs comprises a first distinct extracted feature from one of the plurality of distinct sub-models and a second distinct extracted feature from another of the plurality of distinct sub-models; and \n generates one or more mutuality vectors or one or more relationship vectors based on the extracted mutuality data and/or relationship data between each of the one or more pairs of extracted features.

Metadata:
- Claim Count in Document: 44.0
- Percentile: 97.0
- Lexical Diversity: 2.79661
- Patent Class: 348.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15990212', '13097435', '14195150', '13843455', '14458575']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6006443916729383
- 35 USC 102 Novelty (BERT): 0.484229879645674
- Combined Prediction Score: 0.589002940470212
- Mean Citation Score: 172.018124
- Max Citation Score: 181.93002
- Similarity Product: 124.36064001415372

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