Invention Grant
- Patent Title: Techniques for modeling temporal distortions when predicting perceptual video quality
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Application No.: US15890709Application Date: 2018-02-07
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Publication No.: US10887602B2Publication Date: 2021-01-05
- Inventor: Zhi Li , Christos Bampis
- Applicant: NETFLIX, INC.
- Applicant Address: US CA Los Gatos
- Assignee: NETFLIX, INC.
- Current Assignee: NETFLIX, INC.
- Current Assignee Address: US CA Los Gatos
- Agency: Artegis Law Group, LLP
- Main IPC: H04N19/154
- IPC: H04N19/154 ; H04N19/91 ; H04N21/235 ; G06N3/08 ; G06K9/62 ; G06N3/04 ; G06N20/20 ; G06N20/10 ; G06N5/00 ; H04N17/00

Abstract:
In various embodiments, a prediction application computes a quality score for re-constructed visual content that is derived from visual content. The prediction application generates a frame difference matrix based on two frames included in the re-constructed video content. The prediction application then generates a first entropy matrix based on the frame difference matrix and a first scale. Subsequently, the prediction application computes a first value for a first temporal feature based on the first entropy matrix and a second entropy matrix associated with both the visual content and the first scale. The prediction application computes a quality score for the re-constructed video content based on the first value, a second value for a second temporal feature associated with a second scale, and a machine learning model that is trained using subjective quality scores. The quality score indicates a level of visual quality associated with streamed video content.
Public/Granted literature
- US20190246111A1 TECHNIQUES FOR MODELING TEMPORAL DISTORTIONS WHEN PREDICTING PERCEPTUAL VIDEO QUALITY Public/Granted day:2019-08-08
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