Google Inc.

Waymo LLC

Andrew Crawford

Anil Christopher Kokaram

Damien Kelly

Hugh Denman

Volker Grabe

Sasi Inguva

Stuart Bennett

Colin Andrew Braley

Craig Lewin Robinson

Zachary Morriss

Joan Lasenby

Stephanie McArthur

Neil Birkbeck

Steve Benting

Jeremy Doig

Neil Aylon Charles Birkbeck

Perry Tobin

Ka-kit Lam

Rikard Grunnan

Isasi Inguva

Debargha Mukherjee

Yao-Chung Lin

Francois Pitie

Jiangyang Zhang

Francis Kelly

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 disclosure provides for a method of calibrating a detection system that is mounted on a vehicle. The method includes detecting characteristics of the mirror and characteristics of a vehicle portion using the detection system. The mirror reflects the vehicle portion to be detected using the detection system. The method also includes determining a first transform based on the detected one or more of mirror characteristics, determining a second transform based on the one or more vehicle portion characteristics, and determining a third transform based on a known position of the vehicle portion in relation to the vehicle. Further, the method includes determining a position of the detection system relative to the vehicle based on the first, second, and third transforms and then calibrating the detection system using the determined position of the detection system relative to the vehicle.

Calibration of detection system to vehicle using a mirror

A portable sensor calibration target includes a frame assembly, a first panel, and a second panel. The frame assembly may include three legs and a plurality of frame edges that is configured to form a first frame and a second frame and is configured to be held at a pre-selected height above ground by the legs. The first panel is removably attached to the first frame in an unfolded position, and includes a plurality of boards and a plurality of hinges connecting the plurality of boards. The first panel is configured to fold at the plurality of hinges into a folded position. The second panel is removably attached to the second frame adjacent to the first frame. The first panel and the second panel meet to form an edge, which is detectable by a detection system of a vehicle for calibrating the detection system.

Portable sensor calibration target for autonomous vehicle

The technology relates to fiducials for calibrating or validating a vehicle's sensors. One or more computing devices receive a plurality of data sets captured by the sensors from the plurality of fiducials. Each of the data sets corresponds to a respective sensor of the plurality of sensors. The one or more computing devices determine whether data in each of the plurality of data sets contains expected data representative of a respective fiducial of the plurality of fiducials. For each of the respective sensors, the one or more computing devices output a calibration status or a validation status associated with each data set that contains the expected data representative of the respective fiducial.

Methods of calibrating or validating sensors by using a plurality of fiducials

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.

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 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.

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San Francisco, CA, United States of America

Andrew Crawford