PATENT CLAIM ANALYSIS

Application Number: 16199270
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-04
Patent Classification: ["382", "103000"]

Abstract:
There is provided a method of identifying objects in an image, comprising: extracting query descriptors from the image, comparing each query descriptor with training descriptors for identifying matching training descriptors, each training descriptor is associated with a reference object identifier and with relative location data (distance and direction from a center point of a reference object indicated by the reference object identifier), computing object-regions of the digital image by clustering the query descriptors having common center points defined by the matching training descriptors, each object-region approximately bounding one target object and associated with a center point and a scale relative to a reference object size, wherein the object-regions are computed independently of the identifier of the reference object associated with the object-regions, wherein members of each cluster point toward a common center point, and classifying the target object of each object-region according to the reference object identifier of the cluster.

Claim (Index 11):
The method of  claim 1 , further comprising iterating the computing of the matching training descriptor for each unmatched query descriptor of the second subset of query descriptors, wherein the probability of extending the matching training descriptor from nth closest members of the first subset of query descriptors is mathematically represented as (1\u2212p)pn\u22121, where p denotes the probability of independently ignoring each previously matched query descriptor.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 98.0
- Lexical Diversity: 2.38235
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15594611', '15647292', '13665480', '12324241', '14785045']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3596670378001469
- 35 USC 102 Novelty (BERT): 0.5571185918469584
- Combined Prediction Score: 0.3794121932048281
- Mean Citation Score: 274.372942
- Max Citation Score: 435.78305
- Similarity Product: 367.8442640424967

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

Dataset: test