PATENT CLAIM ANALYSIS

Application Number: 15868374
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-03
Patent Classification: ["382", "115000"]

Abstract:
Systems, robots, and methods for generating three-dimensional skeleton representations of people are disclosed. A method includes generating, from a two-dimensional image, a two-dimensional skeleton representation of a person present in the two-dimensional image. The two-dimensional skeleton representation includes a plurality of joints and a plurality of links between individual joints of the plurality of joints. The method further includes positioning a cone around one or more links of the plurality of links, and identifying points of a depth cloud that intersect with the cone positioned around the one or more links of the two-dimensional skeleton. The points of the depth cloud are generated by a depth sensor and each point provides depth information. The method also includes projecting the two-dimensional skeleton representation into three-dimensional space using the depth information of the points that intersect with the cone, thereby generating the three-dimensional skeleton representation of the person.

Claim (Index 14):
The robot of  claim 12 , further comprising a plurality of sensors communicatively coupled to the processor, wherein the plurality of sensors provide the two-dimensional image.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 86.0
- Lexical Diversity: 2.59016
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15806145', '14119406', '11742609', '13531543', '11572958']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.332704019638327
- 35 USC 102 Novelty (BERT): 0.5012529658703766
- Combined Prediction Score: 0.349558914261532
- Mean Citation Score: 200.691408
- Max Citation Score: 222.18819
- Similarity Product: 138.35562704497576

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