Google Inc.

The Provost, Fellows, Foundation Scholars, and the Other Members of Board, of the College of the Holy and Undivided Trinity of Queen Elizabeth Near Dublin

Anil Christopher Kokaram

Damien Kelly

Andrew Crawford

Hugh Denman

Sasi Inguva

Neil Aylon Charles Birkbeck

Stuart Bennett

Neil Birkbeck

Steve Benting

Joan Lasenby

Jan K Skoglund

Yao-Chung Lin

Jeremy Doig

Perry Tobin

Andrew Hines

Ka-kit Lam

Francois Pitie

Isasi Inguva

Yaowu Xu

Debargha Mukherjee

James Bankoski

Balineedu Adsumilli

Caroline Rebecca Pantofaru

Thor Carpenter

Mohammad Izadi

Chao Chen

Frank Boland

Husain Bengali

Julius Kammerl

Noami A Harte

Naomi Harte

Jiangyang Zhang

Francis Kelly

Balineedu C Adsumilli

Andrew Joseph Crawford

Hugh Pierre Denman

A media items to be shared with users of a content sharing service are identified. Each of the media items corresponds to a video recording generated by a client device that depicts one or more objects corresponding to a real-world event and/or a geographic location. A location of the client device that generated the video recording corresponding to a respective media item of the media items is determined based on image features depicted in a set of frames of the video recording. A request for content associated with at least one of the real-world event and/or the geographic location is received from another client device connected to the content sharing service. The media items and, for each of the media items, an indication of the location of the client device that generated the corresponding video recording are provided in accordance with the request for content.

Determining multiple camera positions from multiple videos

An interactive multi-view module identifies a plurality of media items associated with one or more real-world events. Each of the plurality of media items is created by capturing the real-world events from a particular geographic location. The interactive multi-view module determines a geographic position associated with each of the media items and presents the media items in an interactive multi-view player interface based at least on the geographic positions. The interactive multi-view player interface allows a user to switch between of media items, and indicates at least one of a video density indicating a number of media items available at a given point in time or an event highlight indicating a popularity of the media items at a given point in time. The popularity of the respective media items is determined using one or more factors comprising a number of views of the media items at a given point in time.

Multi-view audio and video interactive playback

A set of media items to be shared with users of a content sharing service is identified. Each of the set of media items corresponds to a video recording generated by a client device that depicts one or more objects corresponding to a real-world event at a geographic location. A positioning of the client device that generated the video recording corresponding to a respective media item of the set of media items is determined. The positioning is determined based on image features depicted in a set of frames of the video recording. A request for content associated with at least one of the real-world event or the geographic location is received from another client device connected to the content sharing service. The set of media items and, for each of the set of media items, an indication of the determined positioning of the client device that generated the corresponding video recording is provided in accordance with the request for content.

The technology disclosed herein includes a method for determining the position of multiple cameras relative to each other. In one example, the method may include: receiving, by a processor, a first video recording of a first camera and a second video recording of a second camera; selecting a set of frames of the first video recording; determining a blurriness measure for multiple frames of the set; identifying feature points in multiple frames of the set; selecting a frame from the set of frames based on the blurriness measure and the identified feature points; and determining a position of a first camera relative to a second camera by comparing the selected frame with a frame of the second video recording.

An interactive multi-view module identifies a plurality of media items associated with a real-world event, each of the plurality of media items comprising a video portion and an audio portion. The interactive multi-view module synchronizes the audio portions of each of the plurality of media items according to a common reference timeline, determines a relative geographic position associated with each of the plurality of media items and presents the plurality of media items in an interactive multi-view player interface based at least on the synchronized audio portions and the relative geographic positions.

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.

Mutual noise estimation for videos

Implementations disclose bitrate optimization for multi-representation encoding using playback statistics. A method includes generating multiple versions of a segment of a source video, the versions comprising encodings of the segment at different encoding bitrates for each resolution of the segment, measuring a quality metric for each version of the segment, generating rate-quality models for each resolution of the segment based on the measured quality metrics corresponding to the resolutions, generating a probability model to predict requesting probabilities that representations of the segment are requested, the probability model based on a joint probability distribution of network speed and viewport size that is generated from client-side feedback statistics associated with prior playbacks of other videos, determining an encoding bitrate for each of the representations of the segment based on the rate-quality models and the probability model, and assigning determined encoding bitrates to corresponding representations of the segment.

Bitrate optimization for multi-representation encoding using playback statistics

A method includes determining whether a rate distortion cost of a compressed video is above a cost threshold, the compressed video being encoded using a first constant rate factor (CRF). Upon determining the quality of a compressed video is above a cost threshold calculating a second CRF based on the first CRF, and encoding a video associated with the compressed video using the second CRF. Upon determining the quality of a compressed video is below a cost threshold encoding the video using the first CRF and a target bitrate.

Adaptive multi-pass video encoder control

Described herein are techniques related to noise reduction for image sequences or videos. This Abstract is submitted with the understanding that it will not be used to interpret or limit the scope and meaning of the claims. A noise reduction tool includes a motion estimator configured to estimated motion in the video, a noise spectrum estimator configured to estimate noise in the video, a shot detector configured to trigger the noise estimation process, a noise spectrum validator configured to validate the estimated noise spectrum, and a noise reducer to reduce noise in the video using the estimated noise spectrum.

Noise reduction for image sequences

Systems and methods are described for identifying the video content as spherical video or non-spherical video in response to determining that frame scores and video scores satisfy a threshold level. For example, a plurality of image frames can be extracted from video content, classified in a dual stage process, and scored according to particular classification and scoring mechanisms.

System and method for automatic detection of spherical video content

A method and system include identifying a plurality of media clips pertaining to an event, for each pair of the plurality of media clips, calculating pairwise relative time offsets for pairs of media clips from the plurality of media clips, calculating, by a processing device, an inconsistency measure, in which the inconsistency measure of a pair of media clips is calculated using at least three relative time offsets and one of the at least three relative time offsets is a relative time offset of the pair of media clips, and synchronizing the plurality of media clips based on resulting calculated inconsistency measures.

Apparatus and method for temporal synchronization of multiple signals

A method for determining the position of multiple cameras relative to each other includes at a processor, receiving video data from at least one video recording taken by each camera; selecting a subset of frames of each video recording, including determining relative blurriness of each frame of each video recording, selecting frames having a lowest relative blurriness, counting features points in each of the lowest relative blurriness frames, and selecting for further analysis, lowest relative blurriness frames having a highest count of feature points; and processing each selected subset of frames from each video recording to estimate the location and orientation of each camera.

A method includes identifying a frame of a spherical video as a key frame, storing a compensation component based on position data of a camera in association with the key frame, and compensating for a movement of the camera in a subsequent frame of the spherical video based on the key frame and the compensation component associated with the key frame.

Spherical video stabilization based on accelerometer data

A method for pull frame interpolation includes receiving an encoded bitstream including information representing a plurality of frames of video data, decoding the plurality of frames, including identifying a plurality of motion vectors indicating motion from a first frame of the plurality of video frames to a second frame of the plurality of video frames, identifying an interpolation point between the first frame and the second frame, identifying a plurality of candidate interpolation motion vectors indicating motion from the first frame to the interpolation point and from the second frame to the interpolation point based on the plurality of motion vectors, selecting an interpolation motion vector from the plurality of candidate interpolation motion vectors based on a metric, and generating an interpolated frame at the interpolation point based on the selected interpolation motion vector, which may include correcting an artifact in the interpolated frame by blending the interpolated frame.

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Santa Clara, CA, United States of America

Anil Christopher Kokaram