PATENT CLAIM ANALYSIS

Application Number: 16022009
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2019-01
Patent Classification: ["345", "419000"]

Abstract:
The present disclosure provides a three-dimensional posture estimating method and apparatus, a device and a computer storage medium, wherein the method comprises: obtaining two-dimensional posture information of an object in an image and three-dimensional size information of the object; determining coordinates of key points of the object in an object coordinate system according to the three-dimensional size information of the object; determining a transformation relationship between a camera coordinate system and the object coordinate system according to a geometrical relationship between coordinates of key points of the object in the object coordinate system and the two-dimensional posture information of the object. Application of this manner to the field of autonomous driving may implement mapping a detection result of a two-dimensional obstacle to a three-dimensional space to obtain its posture.

Claim (Index 14):
The device according to  claim 13 , wherein the method further comprises:\n determining coordinates of the key points of the object in the camera coordinate system, according to coordinates of the key points of the object in the object coordinate system and the transformation relationship.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 94.0
- Lexical Diversity: 2.30508
- Patent Class: 345.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['10995524', '14363102', '15300305', '15250324', '15006322']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6660482058124255
- 35 USC 102 Novelty (BERT): 0.48491755116721
- Combined Prediction Score: 0.647935140347904
- Mean Citation Score: 185.88118000000003
- Max Citation Score: 197.68303
- Similarity Product: 143.46004005137087

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