PATENT CLAIM ANALYSIS

Application Number: 15879432
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-07
Patent Classification: ["386", "280000"]

Abstract:
An immersive computing machine makes a recording of an immersive MR scene. The recording includes sufficient data to reconstruct multiple different three-dimensional views of the scene depending on a perspective of a viewer using another immersive computing machine. One or multiple viewers may enter a playback of the recorded immersive scene and make further immersive recordings. The scene may be a still or a motion scene. The immersive recording is transmitted with a two-dimensional version of the recording that can be viewed on a non-immersive device, which can add the three-dimensional immersive recording to a queue for later viewing on an immersive device.

Claim (Index 13):
The method of  claim 12 , further comprising:\n transmitting sufficient data, from the immersive computing system to the further immersive computing system, for the further immersive computing system to composite the live view of the viewer into the display of the immersive MR scene to the subject; and transmitting sufficient data, from the further immersive computing system to the immersive computing system, for the immersive computing system to composite the live view of the subject into the display of the immersive MR scene to the viewer.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 86.0
- Lexical Diversity: 1.81667
- Patent Class: 386.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15289090', '15289174', '15482120', '15717823', '15141760']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6036624354529011
- 35 USC 102 Novelty (BERT): 0.4868108802211583
- Combined Prediction Score: 0.5919772799297268
- Mean Citation Score: 220.59602200000003
- Max Citation Score: 230.53954
- Similarity Product: 168.61087871304272

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test