PATENT CLAIM ANALYSIS

Application Number: 16287191
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-06
Patent Classification: ["348", "014090"]

Abstract:
In one embodiment, a method is provided to intelligently frame groups of participants in a meeting. This gives a more pleasing experience with fewer switches, better contextual understanding, and more natural framing, as would be seen in a video production made by a human director. Furthermore, in accordance with another embodiment, conversational framing techniques are provided. During speaker tracking, when two local participants are addressing each other, a method is provided to show a close-up framing showing both participants. By evaluating the direction participants are looking and a speaker history, it is determined if there is a local discussion going on, and an appropriate framing is selected to give far-end participants the most contextually rich experience.

Claim (Index 19):
The non-transitory processor readable medium of  claim 18 , wherein, if the second participant was not the previous active speaker, the instructions, when executed by the processor, further cause the processor to:\n determine if the first participant is facing a third participant of the plurality of participants based on the output of the video camera of the video conference endpoint.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 99.0
- Lexical Diversity: 1.61728
- Patent Class: 348.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15908984', '15581120', '15981299', '16005971', '15091056']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6611132835859413
- 35 USC 102 Novelty (BERT): 0.5189523790186711
- Combined Prediction Score: 0.6468971931292143
- Mean Citation Score: 258.732154
- Max Citation Score: 332.9112
- Similarity Product: 288.7371095103264

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