Abstract: Encrypting a document, including: generating first and second nonces; combining the first and second nonces to generate a secret key that is deterministically defined by the first and second nonces; encrypting the document using the secret key to produce an encrypted document; delivering the first nonce to a license manager; and delivering the second nonce to a rights manager.

Abstract: Distributing and enforcing a license for content to be consumed according to conditions defined by usage rights stated in the license, including: encrypting the usage rights with a key using a homomorphic encryption and sending the encrypted usage rights to an agent; receiving from the agent modified encrypted usage rights generated by performing a homomorphic operation on the encrypted usage rights with a nonce; and decrypting the modified encrypted usage rights and sending the decrypted modified usage rights back to the agent, wherein usage rights are extracted from the decrypted modified usage rights by performing an operation that is reverse of the homomorphic operation with the nonce.

Abstract: Video rendering, including: tracking spatial coordinates of at least one camera during a video sequence forming a shot having multiple frames, wherein each of the at least one camera has a lens; creating a lens profile storing lens data corresponding to the lens of the at least one camera during the shot; encoding the lens data; sending the lens data to a render engine; retracing the movement of the at least one camera during the shot; recreating the lens and one or more characteristics of the lens during the shot; and replicating the shot in a virtual environment using the retraced camera movement and recreated lens characteristics.

Abstract: Managing cameras and controlling video display, including: identifying a first group of cameras, each camera in the first group having a respective image stream; identifying a second group of cameras, each camera in the second group having a respective image stream, and each camera in the second group is not in the first group; assigning a name to each group; assigning a name to each camera; displaying the name of each group in a user interface on a computer system; displaying the name of each camera in the user interface; receiving a selection of a group through the user interface; displaying the image stream for each camera in the selected group simultaneously; receiving a selection of one camera through the user interface; and displaying the image stream for the selected camera.

Abstract: Authenticating for a virtual reality (VR) system using a plurality of factors of authentication, including: collecting a password entered into a virtual keyboard for a first factor of the plurality of factors of authentication, wherein the password is entered by a user selecting a series of data including numbers, letters, or images on the virtual keyboard displayed on a display of the VR system; and collecting a biometric fingerprint from movements of the VR system for a second factor of the plurality of factors of authentication.

Abstract: Blockchain-based proof of presentation of content on a media channel, including: generating, upon receiving a request to generate, at least first, second, and third parameters, wherein the first and second parameters are input parameters and the third parameter is calculated as an output parameter of a one-way cryptographic function; generating a first type of block by incorporating the first and third parameters into the first type of block; validating the first type of block and the blockchain; appending the first type of block to the blockchain when both the first type of block and the blockchain are declared valid; and embedding the second parameter into the content that is to be made available on the media channel to produce tainted content.

Abstract: Systems, methods, and apparatus to generate training data include receiving a beam of light reflected from a subject and splitting the beam of light into at least a first beam and a second beam; directing the first beam toward a first sensor and the second beam toward a second sensor; sensing and processing the first beam to generate a first video having a first characteristic; sensing and processing the second beam to generate a second video having a second characteristic; and processing the first video and the second video to generate training data.

Abstract: Verifying that a user is using a device at a pre-specified location between a start time and an end time, including: calculating a challenge and an answer that is a function of the challenge; generating and storing in a blockchain, a commitment including an identity of the user, an identity of the device, the pre-specified location associated with the user, the start time of usage of the device, the end time of usage of the device, and the calculated challenge; generating a visual code of the device to carry the answer; encrypting the generated visual code with a public key of the device, wherein the encrypted visual code may only be decrypted with a private key of the device; and storing the encrypted visual code in the blockchain.

Abstract: Methods, systems, and computer-readable storage medium including: a lens and a focal reducer to receive a beam of image; a beam splitter to receive the beam of image from the focal reducer and split the beam of image into multiple directions. The system also includes a plurality of sensors coupled to the beam splitter. Each sensor of the plurality of sensors is configured to sense the beam of image within a particular band of frequencies. Further, the particular band of frequencies of a first sensor of the plurality of sensors does not overlap with the particular band of frequencies of a second sensor of the plurality of sensors. The focal reducer condenses and amplifies the beam of image to increase the sensitivity of each sensor.

Abstract: Content conversion verification, includes: converting, at a first computer system, an original content file to a target format, generating a converted content file in the target format; generating a checksum for the converted content file; and sending the original content file and the checksum to a second computer system. Key words include content verification and checksum.

Abstract: Enabling control of authenticated applications and websites from other applications and websites within an auto entertainment service, including: implementing controls of the auto entertainment service within a privilege auto platform with a defined structure that enables a controller to issue a command; constructing calls appropriate to execute the command; routing playback controls through the privilege auto platform; issuing the command to the privilege auto platform with a content ID; and receiving the command and making the calls for content and digital rights management to execute the command.

Abstract: Accessing media data in bites, including: receiving a request from a client to access a media item, and determining an address of the requested media item, wherein the address indicates a location where the media item is stored; determining an identification number of a piece of the media item selected by the client; updating the address of the media item by combining the address with the identification number of the piece of the media item selected by the client; valuating the piece of the media item selected by the client, and sending a valuated price to the client; and providing access to the requested media item using the updated address of the media item when a payment for the valuated price is received from the client.

Abstract: Generating a rights blockchain storing rights of a user, including: receiving an enrollment request and a public key from the user; verifying that the user has a private key corresponding to the public key; generating a user identifier using the public key; and generating and delivering the rights blockchain having a genesis block including the user identifier to the user.

Abstract: Improving the accuracy of predicted segmentation masks, including: extracting a ground-truth RGB image buffer and a binary contour image buffer from a ground-truth RGB image container for segmentation training; generating predicted segmentation masks from the ground-truth RGB image buffer; generating second binary contours from the predicted segmentation masks using a particular algorithm; computing a segmentation loss between manually-segmented masks of the ground-truth RGB image buffer and the predicted segmentation masks; computing a contour accuracy loss between contours of the binary contour image buffer and the binary contours of the predicted segmentation masks; computing a total loss as a weighted average of the segmentation loss and the contour accuracy loss; and generating improved binary contours by compensating the contours of the binary contour image buffer with the computed total loss, wherein the improved binary contours are used to improve the accuracy of the predicted segmentation masks.

Abstract: Automatically setting a display mode of a display device, including: receiving a content selection of a content item through a user interface; sending the content selection to a content server; receiving content data from the content server; receiving settings metadata from the content server, wherein the settings metadata indicates a metadata display setting; processing the settings metadata to determine the metadata display settings, wherein the settings metadata is processed to be at least one of: stored in a memory unit of the display device; received with the content data to be processed and used to update the metadata display settings; and associated with at least one application running on the display device; setting a display mode of a display device according to the metadata display setting; and displaying the media content through the display device according to the set display mode.

Abstract: Methods, systems, and apparatus including: first attaching ink lines drawn directly onto characters of the CG animation; first enabling the artist to modify the ink lines using nudges to generate a drawing; first moving the drawing into a UV space and generating first pass training data; second attaching the ink lines onto the characters of the CG animation; second enabling the artist to modify the ink lines; second moving the drawing into the UV space and generating second pass training data; combining the first pass training data and the second pass training data to generate combined data; and creating and outputting a second generation machine learning using the combined data.

Abstract: Video capture of a subject, including: capturing video data of the subject using a first camera; capturing infrared (IR) video data of the subject using a second camera linked to the first camera, in such a manner that the first and second camera share the same field of view, wherein the second camera is sensitive to IR light for capturing the IP video data of the subject; illuminating the subject with at least one IR light source; and processing the video data from the first camera and the IR video data from the second camera to identify an outline of the illuminated subject in the video data using the IR video data.

Abstract: Distributing different resolution point clouds of a full resolution point cloud, including: applying a plurality of sieve functions to the full resolution point cloud (PC) to generate a plurality of partial point clouds (PCs), wherein the partial PCs are disjointed elements of the full resolution PC; scrambling each partial PC of the plurality of partial PCs using a respective one of a plurality of secret keys; and distributing at least one scrambled PC and a selected secret key to an intended recipient, wherein the selected secret key is selected based on an appropriate resolution determined for the intended recipient.

Abstract: Capturing and visualizing video, including: capturing video data using a plurality of cameras; sending the captured video data to a first shader; calculating depth information at the first shader using the captured video data; generating a three-dimensional (3-D) point cloud using the depth information; and rendering a visualization image using the 3-D point cloud.

Abstract: Automatically shifting between virtual lens parameters and optical lens parameters for an optical camera positioned within a physical scene, including: providing a spatial awareness of the physical scene including position and orientation of a display screen to the optical camera; creating a feedback loop between the optical camera and lens to enable the lens to communicate lens settings to a scene registration; determining when focus of the lens is beyond an optical focal limit from the lens settings; and enabling the lens, by the scene registration, to automatically shift from using the optical lens parameters to using the virtual lens parameters when the focus of the lens moves beyond the optical focal limit.