PATENT CLAIM ANALYSIS

Application Number: 16154130
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-06
Patent Classification: ["348", "159000"]

Abstract:
A method of detecting occupants in a vehicle includes detecting an oncoming vehicle and acquiring a plurality of images of occupants in the vehicle in response to detection of the vehicle. The method includes performing automated facial detection on the plurality of images and adding a facial image for each face detected to a gallery of facial images for the occupants of the vehicle. The method includes performing automated facial recognition on the gallery of facial images to group the facial images into groups based on which occupant is in the respective facial images, and counting the final group of unique facial images to determine how many occupants are in the vehicle.

Claim (Index 1):
A method of detecting occupants in a vehicle comprising:\n detecting an oncoming vehicle; acquiring a plurality of images of occupants in the vehicle in response to detection of the vehicle; performing automated facial detection on the plurality of images and adding a facial image for each face detected to a gallery of facial images for the occupants of the vehicle; performing automated facial recognition on the gallery of facial images to group the facial images into groups based on which occupant is in the respective facial images; and counting the groups to determine how many occupants are in the vehicle.

Metadata:
- Claim Count in Document: 27.0
- Percentile: 97.0
- Lexical Diversity: 2.36735
- Patent Class: 348.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15608422', '15924880', '13324308', '10974282', '15505005']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6351582965094585
- 35 USC 102 Novelty (BERT): 0.487351142062399
- Combined Prediction Score: 0.6203775810647526
- Mean Citation Score: 189.693098
- Max Citation Score: 208.92345
- Similarity Product: 148.93653036249873

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

Dataset: test