PATENT CLAIM ANALYSIS

Application Number: 15746568
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-09
Patent Classification: ["382", "165000"]

Abstract:
The application discloses a method and an apparatus for recognizing RGB-D objects based on adaptive similarity measure of dense matching item, wherein the method can include at least the following steps: convolution neural network features of a to-be-queried object and a reference object are extracted; dense matching is carried out on the reference object and the to-be-queried object on the basis of the convolution neural network features fused with RGB and depth information; similarity between the reference object and the to-be-queried object is measured according to a dense matching result; and the to-be-queried object is classified based on the similarity between the reference object and the to-be-queried object. With the embodiments of the present application, at least in part, the technical problem of how to improve the robustness of object recognition is solved.

Claim (Index 1):
A method for recognizing RGB-D objects based on adaptive similarity measure of dense matching item, at least comprising:\n extracting convolution neural network features of a to-be-queried object and a reference object; carrying out dense matching of the reference object and the to-be-queried object on the basis of the convolution neural network features in fusion with RGB and depth information; measuring similarity between the reference object and the to-be-queried object according to a result of the dense matching; and classifying the to-be-queried object based on the similarity between the reference object and the to-be-queried object.

Metadata:
- Claim Count in Document: 3.0
- Percentile: 86.0
- Lexical Diversity: 2.05797
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['16067819', '15038325', '15783908', '12968796', '11365273']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3146819667498776
- 35 USC 102 Novelty (BERT): 0.4856323078118598
- Combined Prediction Score: 0.3317770008560758
- Mean Citation Score: 190.103838
- Max Citation Score: 225.36264
- Similarity Product: 174.09372260971068

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