PATENT CLAIM ANALYSIS

Application Number: 15898160
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-03
Patent Classification: ["345", "419000"]

Abstract:
Methods and systems for change detection utilizing three dimensional (3D) point-cloud processing are provided. The method includes detecting changes in the surface based on a surface fitting approach with a locally weighted Moving Least Squares (MLS) approximation. The method includes acquiring and comparing surface geometry of a reference point-cloud defining a reference surface and a template point-cloud defining a template surface at local regions or local surfaces using the surface fitting approach. The method provides effective change detection for both, rigid as well as non-rigid changes, reducing false detections due to presence of noise and is independent of factors such as texture or illumination of an object or scene being tracked for changed detection.

Claim (Index 1):
A processor implemented method for change detection in a surface represented by 3D point-cloud, the method comprising:\n acquiring a reference point-cloud defining a reference surface and a template point-cloud defining a template surface, wherein the reference point-cloud and the template point-cloud correspond to the 3D point-cloud of the surface acquired at different time instances; aligning the template surface with the reference surface by performing registration of the template point-cloud and the reference point-cloud, wherein the registration of the reference point-cloud and the template point-cloud is based on shape similarity based constraints; equalizing point density of the registered reference point-cloud and the registered template point-cloud by performing subsampling to provide a processed reference point-cloud and a processed template point-cloud; reducing noise from the processed reference point-cloud and the processed template point-cloud by estimating a smooth reference surface and a smooth template surface using a locally weighted Moving Least Squares (MLS) approximation; voxelizing the smooth reference surface to generate a plurality of reference voxels and the smooth template surface to generate a plurality of template voxels, wherein each reference voxel is defined by a plurality of reference vertices and each template voxel is defined by a plurality of template vertices; determining a corresponding reference vertex for every template vertex of each template voxel using a k-dimensional (kd)-tree, wherein the kd-tree is set with the plurality of reference vertices of a reference voxel; and determining vertex distance between every template vertex and the determined corresponding reference vertex, wherein the determined vertex distance above a predefined vertex distance threshold is indicative of the change in the surface represented by the 3D-point-cloud.

Metadata:
- Claim Count in Document: 17.0
- Percentile: 88.0
- Lexical Diversity: 1.58974
- Patent Class: 345.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15729469', '15872557', '14800078', '15349837', '14324891']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5970701161135815
- 35 USC 102 Novelty (BERT): 0.4881269733736729
- Combined Prediction Score: 0.5861758018395906
- Mean Citation Score: 197.96079200000003
- Max Citation Score: 221.77916
- Similarity Product: 177.19975654587742

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

Dataset: test