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 11):
The method of  claim 1 , wherein the immersive MR scene includes a recording of a subject, the method further comprising:\n displaying the immersive MR scene to the subject on a further immersive device connected to a further immersive computing system, simultaneously with the displaying of the immersive MR scene to the viewer; wherein:\n the display of the immersive MR scene to the viewer includes a composited live view of the subject; and \n the display of the immersive MR scene to the subject includes a composited live view of 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): 0.6032056126300134
- 35 USC 102 Novelty (BERT): 0.4888396716334536
- Combined Prediction Score: 0.5917690185303575
- Mean Citation Score: 220.59602200000003
- Max Citation Score: 230.53954
- Similarity Product: 164.34988899463414

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