PATENT CLAIM ANALYSIS

Application Number: 15901888
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-08
Patent Classification: ["345", "156000"]

Abstract:
In a telepresence scenario with remote users discussing a document or a slide, it can be difficult to follow which parts of the document are being discussed. One way to address this problem is to provide feedback by showing where the user's hand is pointing at on the document, which also enables more expressive gestural communication than a simple remote cursor. An important practical problem is how to transmit this remote feedback efficiently with high resolution document images. This is not possible with standard videoconferencing systems which have insufficient resolution. We propose a method based on using hand skeletons to provide the feedback. The skeleton can be captured using a depth camera or a webcam (with a deep network algorithm), and the small data can be transmitted at a high frame rate (without a video codec).

Claim (Index 17):
The computer-implemented method of  claim 1 , wherein the hand of the user is tracked using a deep learning based hand pose estimator.

Metadata:
- Claim Count in Document: 25.0
- Percentile: 88.0
- Lexical Diversity: 1.57895
- Patent Class: 345.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['11204777', '13084950', '14221104', '14447502', '14491671']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6449130228188811
- 35 USC 102 Novelty (BERT): 0.451546587386835
- Combined Prediction Score: 0.6255763792756766
- Mean Citation Score: 133.454178
- Max Citation Score: 143.26924
- Similarity Product: 118.89154588122842

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