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 1):
A machine learning-based system for generating event intelligence from video image data, the system comprising:\n one or more video image data sources that capture live video image data of one or more scenes; a coarse feature extraction model that:\n collects input of the live video image data captured through the one or more video image data sources, the live video image data comprising a plurality of successive image frames of the one or more scenes; \n detects one or more coarse features within the live video image data by performing at least edge detection within the live video image data; \n extracts the one or more coarse features within the live video image data based on results of the edge detection; \n constructs a coarse feature mapping comprising a mapping of the one or more coarse features to each of the plurality of successive image frames of the live video image data; \n an ensemble of distinct machine learning models that:\n receives input of the coarse feature mapping at each of a plurality of distinct sub-models that define the ensemble of distinct machine learning models; \n identifies objects within the live video image data based on the coarse feature mapping; \n identifies one or more activities associated with the objects within the live video image data based on the coarse feature mapping; \n identifies 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; \n a condenser implementing a trained natural language model that:\n composes natural language descriptions based on the one or more activities associated with the objects and the one or more interactions between the objects; \n constructs an intelligence augmented live video image data by superimposing the natural language descriptions onto the live video image data; and \n displays via a user interface system the intelligence augmented live video image data.

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): 0.6001935732792953
- 35 USC 102 Novelty (BERT): 0.4860492793259173
- Combined Prediction Score: 0.5887791438839576
- Mean Citation Score: 172.018124
- Max Citation Score: 181.93002
- Similarity Product: 122.11603395854472

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