Invention Grant
- Patent Title: Techniques for modeling temporal distortions when predicting perceptual video quality
-
Application No.: US17141081Application Date: 2021-01-04
-
Publication No.: US11700383B2Publication Date: 2023-07-11
- 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 ; G06N20/20 ; G06N20/10 ; H04N17/00 ; G06F18/2411 ; G06N3/045 ; G06N5/01

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
- US20210127120A1 TECHNIQUES FOR MODELING TEMPORAL DISTORTIONS WHEN PREDICTING PERCEPTUAL VIDEO QUALITY Public/Granted day:2021-04-29
Information query