PATENT CLAIM ANALYSIS

Application Number: 15872557
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-03
Patent Classification: ["382", "154000"]

Abstract:
Systems and methods of the present disclosure facilitate rigid point cloud registration with characteristics including shape constraint, translation proportional to distance and spatial point-set distribution model for handling scale. The method of the present disclosure enables registration of a rigid template point cloud to a given reference point cloud. Shape-constrained gravitation, as induced by the reference point cloud, controls movement of the template point cloud such that at each iteration, the template point cloud better aligns with the reference point cloud in terms of shape. This enables alignment in difficult conditions introduced by change such as presence of outliers and/or missing parts, translation, rotation and scaling. Also, systems and methods of the present disclosure provide an automated method as against conventional methods that depended on manually adjusted parameters.

Claim (Index 11):
A computer program product comprising a non-transitory computer readable medium having a computer readable program embodied therein, wherein the computer readable program, when executed on a computing device, causes the computing device to:\n capture a reference point cloud and a template point cloud; and automatically perform rigid registration of the reference point cloud and the template point cloud by:\n embedding a shape-based similarity constraint into a Gravitational Approach (GA), wherein curvature is used for representation of shape; \n iteratively performing:\n obtaining total force applied on a point of the template point cloud by all points on the reference point cloud; \n computing translation of the template point cloud based on the obtained total force to obtain new position of the template point cloud with respect to the reference point cloud; \n estimating rotation required for the rigid registration based on the new position of each point of the template point cloud; and \n estimating scaling required for the rigid registration based on a ratio of eigenvalues of co-variance matrices associated with the reference point cloud and the template point cloud.

Metadata:
- Claim Count in Document: 6.0
- Percentile: 86.0
- Lexical Diversity: 1.79487
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['14604829', '11259560', '14324891', '15368351', '15233856']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2523364438615697
- 35 USC 102 Novelty (BERT): 0.4784294241191312
- Combined Prediction Score: 0.2749457418873259
- Mean Citation Score: 137.07732600000003
- Max Citation Score: 142.38763
- Similarity Product: 100.298610819723

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

Dataset: test