公开(公告)号：WO2018222240A1

公开(公告)日：2018-12-06

申请号：PCT/US2018/021840

申请日：2018-03-09

Applicant: GOOGLE LLC

Inventor： BIRKBECK, Neil ,  IZADI, Mohammad ,  KOKARAM, Anil ,  ADSUMILLI, Balineedu, C. ,  KELLY, Damien

IPC: G06T5/00

Abstract: Implementations disclose mutual noise estimation for videos. A method includes determining an optimal frame noise variance for intensity values of each frame of frames of a video, the optimal frame noise variance based on a determined relationship between spatial variance and temporal variance of the intensity values of homogeneous blocks in the frame, identifying an optimal video noise variance for the video based on optimal frame noise variances of the frames of the video, selecting, for each frame of the video, one or more of the blocks having a spatial variance that is less than the optimal video noise variance, the one or more frames selected as the homogeneous blocks, and utilizing the selected homogeneous blocks to estimate a noise signal of the video.

公开(公告)号：WO2019117866A1

公开(公告)日：2019-06-20

申请号：PCT/US2017/065794

申请日：2017-12-12

Applicant: GOOGLE LLC

Inventor： BIRKBECK, Neil ,  ADSUMILLI, Balineedu ,  KELLY, Damien

IPC: H04N21/233 ,  H04N21/234 ,  H04N21/2343 ,  H04N21/4728 ,  H04N21/81

CPC classification number: H04N21/816 ,  H04N21/233 ,  H04N21/23418 ,  H04N21/234345 ,  H04N21/23439 ,  H04N21/4728 ,  H04N21/812

Abstract: Signals of an immersive multimedia item are jointly considered for optimizing the quality of experience for the immersive multimedia item. During encoding, portions of available bitrate are allocated to the signals (e.g., a video signal and an audio signal) according to the overall contribution of those signals to the immersive experience for the immersive multimedia item. For example, in the spatial dimension, multimedia signals are processed to determine spatial regions of the immersive multimedia item to render using greater bitrate allocations, such as based on locations of audio content of interest, video content of interest, or both. In another example, in the temporal dimension, multimedia signals are processed in time intervals to adjust allocations of bitrate between the signals based on the relative importance of such signals during those time intervals. Other techniques for bitrate optimizations for immersive multimedia streaming are also described herein.

公开(公告)号：WO2019112544A1

公开(公告)日：2019-06-13

申请号：PCT/US2017/064416

申请日：2017-12-04

Applicant: GOOGLE LLC

Inventor： KELLY, Damien ,  BIRKBECK, Neil ,  ADSUMILLI, Balineedu ,  IZADI, Mohammad

IPC: G06T5/00 ,  G06T5/10

CPC classification number: G06T5/002 ,  G06T5/10 ,  G06T2207/20021 ,  G06T2207/20056

Abstract: A method for denoising video content includes identifying a first frame block associated with a first frame of the video content. The method also includes estimating a first noise model that represents characteristics of the first frame block. The method also includes identifying at least one frame block adjacent to the first frame block. The method also includes generating a second noise model that represents characteristics of the at least one frame block adjacent to the first frame block by adjusting the first noise model based on at least one characteristic of the at least one frame block adjacent to the first frame block. The method also includes denoising the at least one frame block adjacent to the first frame block using the second noise model.

公开(公告)号：WO2022261203A1

公开(公告)日：2022-12-15

申请号：PCT/US2022/032668

申请日：2022-06-08

Applicant: GOOGLE LLC

Inventor： WANG, Yilin ,  ADSUMILLI, Balineedu ,  KE, Junjie ,  TALEBI, Hossein ,  YIM, Joong ,  BIRKBECK, Neil ,  MILANFAR, Peyman ,  YANG, Feng

IPC: H04N21/234 ,  H04N21/266

Abstract: Methods, systems, and media for determining perceptual quality indicators of video content items are provided. In some embodiments, the method comprises: receiving a video content item; extracting a plurality of frames from the video content item; determining, using a first subnetwork of a deep neural network, a content quality indicator for each frame of the plurality of frames of the video content item; determining, using a second subnetwork of the deep neural network, a video distortion indicator for each frame of the plurality of frames of the video content item; determining, using a third subnetwork of the deep neural network, a compression sensitivity indicator for each frame of the plurality of frames of the video content item; generating a quality level for each frame of the plurality of frames of the video content item that concatenates the content quality indicator, the video distortion indicator, and the compression sensitivity indicator for that frame of the video content item; generating an overall quality level for video content item by aggregating the quality level of each frame of the plurality of frames; and causing a video recommendation to be presented based on the overall quality level of the video content item.

公开(公告)号：WO2019112558A1

公开(公告)日：2019-06-13

申请号：PCT/US2017/064621

申请日：2017-12-05

Applicant: GOOGLE LLC

Inventor： BIRKBECK, Neil ,  ADSUMILLI, Balineedu ,  IZADI, Mohammad

IPC: G06T5/00

CPC classification number: G06T5/002 ,  G06T2207/10016

Abstract: A method for denoising video content includes identifying a first frame block of a plurality of frame blocks associated with a first frame of the video content. The method also includes determining an average intensity value for the first frame block. The method also includes determining a first noise model that represents characteristics of the first frame block. The method also includes generating a denoising function using the average intensity value and the first noise model for the first frame block. The method further includes denoising the plurality of frame blocks using the denoising function.