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US Patent 12137230 Method and apparatus for applying deep learning techniques in video coding, restoration and video quality analysis (VQA)

Patent 12137230 was granted and assigned to Fastvdo Llc on November, 2024 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
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Patent attributes

Patent Applicant
Fastvdo Llc
Fastvdo Llc
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Current Assignee
Fastvdo Llc
Fastvdo Llc
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
121372300
Patent Inventor Names
Madhu Peringassery Krishnan0
Wei Dai0
Pankaj N. Topiwala0
Date of Patent
November 5, 2024
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Patent Application Number
177222570
Date Filed
April 15, 2022
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Patent Citations
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US Patent 10225607 Video processing apparatus and video processing method thereof
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US Patent 9524028 Visual language for human computer interfaces
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US Patent 9829984 Motion-assisted visual language for human computer interfaces
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US Patent 11202103 Techniques for limiting the influence of image enhancement operations on perceptual video quality estimations
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Patent Primary Examiner
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Fernando Alcon
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CPC Code
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G06T 7/0002
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G06T 9/002
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G06T 3/4046
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G06T 2207/20084
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G06T 2207/20081
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G06N 3/08
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H04N 19/567
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H04N 21/23418
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Patent abstract

Video quality analysis may be used in many multimedia transmission and communication applications, such as encoder optimization, stream selection, and/or video reconstruction. An objective VQA metric that accurately reflects the quality of processed video relative to a source unprocessed video may take into account both spatial measures and temporal, motion-based measures when evaluating the processed video. Temporal measures may include differential motion metrics indicating a difference between a frame difference of a plurality of frames of the processed video relative to that of a corresponding plurality of frames of the source video. In addition, neural networks and deep learning techniques can be used to develop additional improved VQA metrics that take into account both spatial and temporal aspects of the processed and unprocessed videos.

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