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: 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.

Abstract: Calibrating cameras in a rig, including: projecting light patterns onto surfaces of objects in a capture volume; capturing image data of the light patterns projected onto the surfaces of the objects using the cameras; and processing the captured image data to estimate a calibration data of the cameras, wherein processing the image data to estimate the calibration data includes measuring distortions in the light patterns.

Abstract: Signing data so that a signature can be verified by a verifier while preserving the privacy of a signer, the method including: generating a signature nonce; encrypting the signature nonce with a public key of the verifier to produce an encrypted signature nonce; and calculating a signature of the data of the signer by signing the data concatenated with the signature nonce using a private key of the signer.

Abstract: Visually enrolling a camera using an optical code and a picture file, including: receiving the picture file and the optical code from the camera, wherein the optical code includes a public key of the camera; generating a visual challenge using a nonce created by a random number generator; transmitting the visual challenge to a user of the camera to capture the visual challenge; receiving the captured visual challenge from the camera; extracting a response from the captured visual challenge; comparing the response to the nonce to verify a signature of the captured visual challenge using the public key of the camera and to convert the optical code received from the camera into a valid certificate; and enrolling the camera and adding the valid certificate to a key store.

Abstract: Enabling colorization and color adjustments on 3D point clouds, which are projected onto a 2D view with an equirectangular projection. A user may color regions on the 2D view and preview the changes immediately in a 3D view of the point cloud. Embodiments render the color of each point in the point cloud by testing whether the 2D projection of the point is inside the colored region. Applications may include generation of a color 3D virtual reality environment using point clouds and color-adjusted imagery.

Abstract: Managing volumetric data, including: defining a view volume in a volume of space, wherein the volumetric data has multiple points in the volume of space and at least one point is in the view volume and at least one point is not in the view volume; defining a grid in the volume of space, the grid having multiple cells and dividing the volume of space into respective cells, wherein each point has a corresponding cell in the grid, and each cell in the grid has zero or more corresponding points; and reducing the number of points for a cell in the grid where that cell is outside the view volume.

Abstract: Enhancing color reproduction of an image in an upscaling process, the method comprising: converting RGB-formatted data into luminance channel formatted data and color channel formatted data; converting RGB-predicted data into luminance channel predicted data and a color channel predicted data; computing a first loss between the RGB-formatted data and the RGB-predicted data; computing a second loss between the color channel formatted data and the color channel predicted data; and outputting a weighted average value of the first loss and the second loss to enhance the color reproduction of the image.

Abstract: Processing a genuine instance of a digital good using a blockchain including: registering an ownership of the genuine instance using a plurality of transactions, the genuine instance uniquely identified by a content descriptor which is cryptographically linked to an ownership token and includes intrinsic characteristics of the genuine instance, wherein the ownership token includes a token seed and a token signature; validating each transaction of the plurality of transactions by a plurality of validators; and recording that the genuine instance belongs to an owner by recording each transaction of the plurality of transactions in the blockchain once each transaction has been validated.

Abstract: Managing device settings on multiple devices, including: creating a first group of devices including two or more devices, wherein each device in the first group has at least one first device setting; creating a second group of devices including two or more devices, wherein each device in the second group has at least one second device setting and each device in the second group is not in the first group; sending the at least one first device setting to each device in the first group of devices in parallel, so that each device in the first group changes at least one device setting according to the at least one received first device setting; and sending the at least one second device setting to each device in the second group of devices in parallel, so that each device in the second group changes at least one device setting according to the at least one received second device setting.