PATENT CLAIM ANALYSIS

Application Number: 15980495
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2019-11
Patent Classification: ["348", "345000"]

Abstract:
An apparatus and method for improving camera depth estimations for a moving subject in the camera field of view. The camera utilizes a generative adversarial network (GAN) to predict future frames from a current frame(s). These predicted future frames are then utilized as a target for determining a depth map from which lens focusing direction and distance are determined for moving the camera into proper focus and thus reducing focusing errors on captured frames as target and/or camera motion progresses.

Claim (Index 6):
A method for adjusting depth of focus in response to predicting future frames, comprising:\n (a) capturing digital images utilizing an autofocus process based on estimating depth of focus based on blur differences between images in a blur matching process; (b) selecting a moving focus target region, which is tracked by a recognition process, at the current frame captured by an image sensor within a device configured for capturing digital images utilizing an autofocus enhanced passive depth estimation process; (c) generating estimations of at least one future frame utilizing a generative adversarial network (GAN) executing on a processor which is executing programming from a memory; (d) generating a depth map between said current frame and said at least one future frame in predicting future depth information while taking into account a period of time required for moving the focusing device to the moving focus target; (e) determining direction and distance for adjusting a focusing device coupled to the image sensor to auto focus on the moving focus target region; and (f) moving said focusing device toward achieving a proper focus at said at least one future frame to update focus position of the selected moving focus target region.

Metadata:
- Claim Count in Document: 15.0
- Percentile: 93.0
- Lexical Diversity: 1.46667
- Patent Class: 348.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14675287', '13077677', '13350285', '12643802', '13609155']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6052869685956382
- 35 USC 102 Novelty (BERT): 0.467124296662517
- Combined Prediction Score: 0.591470701402326
- Mean Citation Score: 160.67146199999996
- Max Citation Score: 173.27358999999996
- Similarity Product: 135.23634902199504

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