Verizon Patent and Licensing Inc.

Sun Microsystems, Inc.

Other

Flipboard, Inc.

Dell Products Inc.

Tivo Corporation

Bmc Software, Inc.

Tivo Solutions Inc.

Marimba, Inc.

Adeia Media Solutions Inc.

Filpboard, Inc.

Jaunt Inc.

Verzon Patent and Licensing Ine.

Arthur A Van Hoff

Thomas M Annau

Jens Christensen

Koji Gardiner

Punit Govenji

Mark A Ross

James Dunn

James M Barton

Daniel Kopeinigg

Timothy Bucher

Timothy Conrad Nichols

Andrew Walkingshaw

Anatoli Adamov

Andrew David Walkingshaw

Maurice Balick

Boris Lev Aleksandrovsky

Clare Lawson

Markus Breunig

Simion Venshtain

Alan Michael Snyder

Mark W Hapner

Simon Wynn

Solmaz Hajmohammadi

Johan Eriksson

Sourabh Khire

Olaf Brandt

Christopher Redmann

Philip Lee

William N Joy

James A Gosling

David Zachary Creemer

Frank N Yellin

Sami Shaio

David M Brownell

Rafael Bracho

Anatoly D Adamov

James Francis Dunn

Jens Bagger Christensen

Rod J McChesney

Aleksandr O Ryzhov

Graham Hamilton

Marcos A Weskamp

Eric I Feng

Johan Prag

Jonathan Payne

Marianne Mueller

Raphael Bracho

Eric Alexander

Roderick J McChesney

Raphael Mauro Schaad

Adam P Gaige

Chris P Redmann

Sarah E Parks

Roderick J Mc Chesney

Charles LePere

A method and apparatus for secure transfer and playback of multimedia content enables the secure transfer of multimedia content from a digital video recorder (DVR) to a personal computer (PC) and further to a handheld device. A DVR determines which devices on a Local Area Network (LAN) are authorized to share and/or retrieve content from the DVR. The DVR receives a connection request from a PC on the LAN, authorizes the connection request and establishes a secure connection between the DVR and the PC. Once the secure connection is established, the DVR receives a request for multimedia content from the PC, prepares the multimedia content for transfer and transfers the multimedia content to the PC.

Method and apparatus for secure transfer and playback of multimedia content

An illustrative system constructs a map that associates pixel locations in a panoramic image to camera modules in a set of camera modules. The map may associate a first pixel location in the panoramic image to a first camera module in the set of camera modules and a second pixel location in the panoramic image to a second camera module in the set of camera modules. The second pixel location borders the first pixel location in the panoramic image. The system blends, based on at least one weight, a pixel value of the first pixel location captured by the first camera module with a pixel value of the second pixel location captured by the second camera module to determine a pixel value for a blended pixel in the panoramic image.

Aggregating images to generate content

Illustrative methods and systems for generating virtual reality content based on corrections to stitching errors are described. An illustrative computer-implemented method includes receiving raw virtual reality video data representing images recorded by camera modules of a camera array, using a stitching algorithm to stitch the images together to generate an initial virtual reality render, determining that the initial virtual reality render has a stitching error, determining a correction for the stitching error, and modifying the stitching algorithm based on the correction for the stitching error. The modified stitching algorithm may be used to generate a corrected virtual reality render that corrects the stitching error.

Generating virtual reality content based on corrections to stitching errors

An illustrative volumetric capture system accesses a machine learning model associated with bodies of a particular body type, as well as a two-dimensional (2D) image captured by a capture device located at a real-world scene. The 2D image depicts a body of the particular body type that is present at the real-world scene. Using the machine learning model and based on the 2D image, the volumetric capture system identifies a 2D joint location, from a perspective of the capture device, of a particular joint of the body. The volumetric capture system also generates a three-dimensional (3D) reference model of the body that represents the particular joint of the body at a 3D joint location that is determined based on the 2D joint location identified using the machine learning model. Corresponding methods and systems are also disclosed.

Methods and systems for applying machine learning to volumetric capture of a body in a real-world scene

An exemplary three-dimensional (3D) simulation system accesses a two-dimensional (2D) video image captured by a video capture device and that depicts a bounded real-world scene and a real-world object present within the bounded real-world scene. The 3D simulation system accesses respective 3D models of the bounded real-world scene and the real-world object. Based on the 2D video image, the 3D simulation system tracks a spatial characteristic of the real-world object relative to the bounded real-world scene. Based on the tracked spatial characteristic of the real-world object and the 3D models of the bounded real-world scene and the real-world object, the 3D simulation system generates a 3D simulation of the bounded real-world scene within which the real-world object is simulated in accordance with the tracked spatial characteristic of the real-world object. Corresponding methods and systems are also disclosed.

Methods and systems for performing 3D simulation based on a 2D video image

The disclosure includes a system and method for generating virtual reality content. For example, the disclosure includes a method for generating virtual reality content that includes a stream of three-dimensional video data and a stream of three-dimensional audio data with a processor-based computing device programmed to perform the generating, providing the virtual reality content to a user, detecting a location of the user's gaze at the virtual reality content, and suggesting an advertisement based on the location of the user's gaze. Another example includes receiving virtual reality content that includes a stream of three-dimensional video data and a stream of three-dimensional audio data to a first user with a processor-based computing device programmed to perform the receiving, generating a social network for the first user, and generating a social graph that includes user interactions with the virtual reality content.

Generating content for a virtual reality system

A method includes receiving two-dimensional video streams from a plurality of cameras, the two-dimensional video streams including multiple angles of a sporting event. The method further includes determining boundaries of the sporting event from the two-dimensional video streams. The method further includes identifying a location of a sporting object during the sporting event. The method further includes identifying one or more players in the sporting event. The method further includes identifying poses of each of the one or more players during the sporting event. The method further includes generating a three-dimensional model of the sporting event based on the boundaries of the sporting event, the location of the sporting object during the sporting event, and the poses of each of the one or more players during the sporting event. The method further includes generating a simulation of the three-dimensional model.

Generating three-dimensional content from two-dimensional images

The disclosure includes a camera array comprising camera modules, the camera modules comprising a master camera that includes a processor, a memory, a sensor, a lens, a status indicator, and a switch, the switch configured to instruct each of the camera modules to initiate a start operation to start recording video data using the lens and the sensor in the other camera modules and the switch configured to instruct each of the camera modules to initiate a stop operation to stop recording, the status indicator configured to indicate a status of at least one of the camera modules. Lens distortion effects may be removed from the frames described by the video data. The camera modules of the camera array are configured to provide a 3&#xd7; field of view overlap.

Camera array removing lens distortion

Systems and methods are disclosed to receive a request for a virtual reality render project that includes information specifying virtual reality video data to be used to create a virtual reality render; determine a plurality of virtual reality jobs required to create the virtual reality render from the virtual reality video data; determine the availability of a plurality of virtual reality nodes across the network; create a virtual reality render map that specifies a processing sequence of the plurality of virtual reality jobs across the one or more virtual reality nodes to create the virtual reality render, the virtual reality render map being created based on at least the availability of the plurality of virtual reality nodes; and process the plurality of virtual reality jobs at the plurality of virtual reality nodes to create the virtual reality.

Virtual reality resource scheduling of processes in a cloud-based virtual reality processing system

The disclosure includes a camera array comprising camera modules, the camera modules comprising a master camera that includes a processor, a memory, a sensor, a lens, a status indicator, and a switch, the switch configured to instruct each of the camera modules to initiate a start operation to start recording video data using the lens and the sensor in the other camera modules and the switch configured to instruct each of the camera modules to initiate a stop operation to stop recording, the status indicator configured to indicate a status of at least one of the camera modules.

Camera array including camera modules

A method includes receiving head-tracking data that describe one or more positions of people while the people are viewing a three-dimensional video. The method further includes generating a probabilistic model of the one or more positions of the people based on the head-tracking data, wherein the probabilistic model identifies a probability of a viewer looking in a particular direction as a function of time. The method further includes generating video segments from the three-dimensional video. The method further includes, for each of the video segments: determining a directional encoding format that projects latitudes and longitudes of locations of a surface of a sphere onto locations on a plane, determining a cost function that identifies a region of interest on the plane based on the probabilistic model, and generating optimal segment parameters that minimize a sum-over position for the region of interest.

Probabilistic model to compress images for three-dimensional video

The disclosure includes generating a stream of panoramic images. A method includes determining a first matching camera module. The method includes constructing a first camera map that associates a first pixel location in a first panoramic image to the first matching camera module, wherein the first pixel location corresponds to the point in a panorama from a first viewing direction. The method includes generating, based on the first camera map, a stream of first panoramic images.

Aggregating images and audio data to generate content

Illustrative methods and systems for generating virtual reality content based on corrections to stitching errors are described. An illustrative computer-implemented method includes receiving raw virtual reality video data representing images recorded by camera modules of a camera array, stitching the images together to generate an initial virtual reality render, determining that the initial virtual reality render has a stitching error, and generating a corrected virtual reality render that corrects the stitching error.

Growing community of inventors

Mountain View, CA, United States of America

Arthur A Van Hoff