PATENT CLAIM ANALYSIS

Application Number: 16020245
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2019-04
Patent Classification: ["345", "156000"]

Abstract:
This disclosure relates generally to hand-gesture recognition, and more particularly to system and method for detecting interaction of 3D dynamic hand gestures with frugal AR devices. In one embodiment, a method for hand-gesture recognition includes receiving frames of a media stream of a scene captured from a FPV of a user using RGB sensor communicably coupled to a wearable AR device. The media stream includes RGB image data associated with the frames of the scene. The scene comprises a dynamic hand gesture performed by the user. Temporal information associated with the dynamic hand gesture is estimated from the RGB image data by using a deep learning model. The estimated temporal information is associated with hand poses of the user and comprises key-points identified on user's hand in the frames. Based on said temporal information, the dynamic hand gesture is classified into predefined gesture classes by using multi-layered LSTM classification network.

Claim (Index 17):
A non-transitory computer-readable medium having embodied thereon a computer program for executing a method for hand-gesture recognition, the method comprising:\n receiving, via one or more hardware processors, a plurality of frames of a media stream of a scene captured from a first person view (FPV) of a user using at least one RGB sensor communicably coupled to a wearable Augmented reality (AR) device, the media stream comprising RGB image data associated with the plurality of frames of the scene, the scene comprising a dynamic hand gesture performed by the user; estimating, via the one or more hardware processors, a temporal information associated with the dynamic hand gesture from the RGB image data by using a deep learning model, the estimated temporal information being associated with hand poses of the user and comprising a plurality of key-points identified on user's hand in the plurality of frames; and classifying, by using a multi-layered Long Short Term memory (LSTM) classification network, the dynamic hand gesture into at least one predefined gesture class based on the temporal information associated with the plurality of key points, via the one or more hardware processors.

Metadata:
- Claim Count in Document: 21.0
- Percentile: 94.0
- Lexical Diversity: 2.0125
- Patent Class: 345.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15402128', '11586750', '15671118', '13428727', '15202750']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6340447607709796
- 35 USC 102 Novelty (BERT): 0.4810119902390131
- Combined Prediction Score: 0.6187414837177829
- Mean Citation Score: 190.373316
- Max Citation Score: 205.43462
- Similarity Product: 155.4614828766024

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