PATENT CLAIM ANALYSIS

Application Number: 16049322
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2018-11
Patent Classification: ["382", "118000"]

Abstract:
Methods and systems for recognizing people in images with increased accuracy are disclosed. In particular, the methods and systems divide images into a plurality of clusters based on common characteristics of the images. The methods and systems also determine an image cluster to which an image with an unknown person instance most corresponds. One or more embodiments determine a probability that the unknown person instance is each known person instance in the image cluster using a trained cluster classifier of the image cluster. Optionally, the methods and systems determine context weights for each combination of an unknown person instance and each known person instance using a conditional random field algorithm based on a plurality of context cues associated with the unknown person instance and the known person instances. The methods and systems calculate a contextual probability based on the cluster-based probabilities and context weights to identify the unknown person instance.

Claim (Index 19):
The system as recited in  claim 16 , further comprising instructions that, when executed by the at least one processor, cause the system to:\n update the context cues based on the identified first unknown person instance; and identify the second unknown person instance in the image based on the updated context cues.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 95.0
- Lexical Diversity: 2.25714
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14945198', '15723144', '13167407', '14279184', '14308181']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2801843790456418
- 35 USC 102 Novelty (BERT): 0.5688898230379444
- Combined Prediction Score: 0.3090549234448721
- Mean Citation Score: 250.39801
- Max Citation Score: 467.1596
- Similarity Product: 346.15465314064033

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test