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 14):
The system of  claim 13 , wherein the one or more hardware processors are further configured by the instructions to test the LSTM classification network for classifying the dynamic hand gesture from amongst the plurality of dynamic hand gestures, wherein to test the LSTM classification network, the one or more hardware processors are further configured by the instructions to:\n interpret, by using a softmax activation function, output scores as unnormalized log probabilities and squashing the output scores to be between 0 and 1 using the following equation: \u03c3 \ue8a0 ( s ) j = e s j \u2211 k = 0 K - 1 \ue89e e s k where,\n K denotes number of classes, s is a K\u00d71 vector of scores, an input to softmax function, and \n j is an index varying from 0 to K\u22121, and \u03c3(s) is K\u00d71 output vector denoting the posterior probabilities associated with each of the plurality of dynamic hand gestures.

Metadata:
- Claim Count in Document: 21.0
- Percentile: 94.0
- Lexical Diversity: 2.0125
- Patent Class: 345.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15402128', '11586750', '15671118', '13428727', '15202750']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6571487777399176
- 35 USC 102 Novelty (BERT): 0.5012804534686038
- Combined Prediction Score: 0.6415619453127863
- Mean Citation Score: 190.373316
- Max Citation Score: 205.43462
- Similarity Product: 126.90299753123402

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