Abstract: Systems and methods provide techniques for reviewing content, such as reviewing video on a mobile device. A computing device with a touch screen interface, e.g., a tablet computer, executes a reviewing tool, e.g., a computer program, that causes the device to display video content and information about the video content. The tool provides an interface for selecting video, images, and information, for review and for annotation. The tool uses remote and/or local data to display video, images, and information for review.

Abstract: Methods and systems including: applying a gamma adjustment to frames of an input video with particular values of parameters to generate at least one set of gamma-adjusted frames to generate at least one set of gamma-adjusted frames; applying a segmentation technique to the at least one set of gamma-adjusted frames to generate segmentation masks; applying an optical flow technique to the at least one set of the gamma-adjusted frames to generate optical flow maps; and combining the segmentation masks and the optical flow maps to generate hybrid segmentation masks.

Abstract: Scrambling a point cloud (PC), including: receiving the PC in polar coordinates, wherein each point of the PC includes an index; scrambling each point of the PC by translating each point along a radial axis of the polar coordinates by adding a pseudo-random number (PRN) to each point, wherein the PRN is generated using the index and a secret key.

Abstract: Linking a consumption history of media to a consumer, including: creating a profile of the consumer using a blockchain-based media ledger; enabling the consumer to subscribe to advertisement networks; recording at least one of consumptions of the media and transactions by the consumer as a media consumption history on a content catalog of a digital right management (DRM); and ingesting the media consumption history into the blockchain-based media ledger from the content catalog of the DRM. Keywords include blockchain, advertising, cryptographic tokens, and DRM.

Abstract: Capturing data from a camera rig including a plurality of sensors to capture data during a capture period, including: a plurality of image sensors including at least a visible light sensor and an infrared (IR) sensor, the plurality of image sensors configured to have a common center line through a single lens; a plurality of light sources including a visible light source and an IR source, wherein the IR source projects an IR beam of a calibration pattern; and a processor coupled to the plurality of image sensors and the plurality of light sources, wherein the processor is configured to process data captured by the visible light sensor, and wherein the processor is configured to process data captured by the IR sensor.

Abstract: Generating a screen-tone look image for a video, including: receiving a smooth gradation rendered image and position information of pixels in the rendered image; generating a pattern for each pixel of the pixels in the rendered image using the position information; dividing the rendered image into a fixed number of sections defined by luminance to produce a luminance gradient image; and applying the patterns to the fixed number of sections of the luminance gradient image.

Abstract: Frame handling an input image in an ML-based upscaling process to produce an output image, including: detecting and extracting boxing edge regions from edges of an active picture area of the input image; extending the extracted boxing edge regions by adding extra pixels around each of the boxing edge regions to produce padded edge regions; upscaling the padded edge regions to produce upscaled padded edge regions; cropping each of the upscaled padded edge regions to a size corresponding to the size of each of the boxing edge regions prior to the upscaling multiplied by an upscaling factor; inserting the cropped edge regions into the edges of the output image; and upscaling a non-edge region of the input image and inserting the upscaled non-edge region into the output image.

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: Training and upscaling a large-sized input image, including: dividing the large-sized input image into a plurality of small-sized sub-pictures; expanding each sub-picture of the plurality of small-sized sub-pictures using target padding pixels to produce an expanded sub-picture; upscaling each sub-picture using an ML-based upscaler to produce an expanded upscaled sub-picture; cropping the expanded upscaled sub-picture to an upscaled size equal to an original size of each sub-picture multiplied by an upscaling factor; repeating expanding, upscaling, and cropping for the plurality of sub-pictures; and concatenating the plurality of cropped sub-pictures to produce an output image.

Abstract: Enabling adjustment of sharpness and details of an input image in upscaling, including: applying a Fourier transform function on a brightness channel of the input image to generate a 2-D frequency map; adjusting the 2-D frequency map to control a target amount of sharpness and details in an upscaled output image; and using the adjusted 2-D frequency map as an additional input channel along with standard color image data for a training and upscaling process.

Abstract: Image capturing, including: generating a pattern of light projection to be projected during non-video capture segments, wherein the pattern of light projection is not projected during video capture segments; determining timing of the non-video capture segments; projecting the generated pattern of light onto a capture volume during the non-video capture segments for a period less than a length of one non-video capture segment; capturing image data of the projected pattern of light using at least one image sensor; and processing the captured image data to obtain information about objects and people in the capture volume.

Abstract: Generating a look of characters using visible brush strokes, including: receiving an input image and a pattern image; replacing each patch in the pattern image with an average color of pixels in the input image corresponding to pixels of each patch to produce a color-averaged output; and applying distortion to the color-averaged output using a distortion image.

Abstract: Systems and methods disclosed include a multiple step process in providing a visual or audiovisual experience, with the multiple steps providing a combination of different types of interactive visual or audiovisual experiences. By combining different types of experiences in this way, the user interactive visual experience is made significantly more interesting to a user. In addition, by linking multiple experiences in this way, the benefits of multiple experiences are gained while reducing the technological processing power required to create the experiences.

Abstract: Video processing, including: generating first tracking information using a first tracking system coupled to a camera which moves during a video sequence forming a shot including multiple frames, wherein the first tracking information includes information about six degrees of freedom motion of the camera synchronized to the multiple frames in the shot; generating second tracking information using a second tracking system coupled to the camera which moves during the video sequence, wherein the second tracking information includes information about six degrees of freedom motion of the camera synchronized to the multiple frames in the shot; generating, by a tracking tool, a timeline with a first track for the first tracking information and a second track for the second tracking information, wherein the tracking tool is coupled to the first tracking system and the second tracking system, and receives the first tracking information and the second tracking information.

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: Verifying that a first device is in a claimed location including: requesting the first device to display a device location identifier (DLI) on a display; sending a request to a second device to: (1) capture the DLI displayed on the display; (2) receive inputs from at least one positioning system and the captured DLI; and (3) output a location proof using the inputs; and receiving the location proof to initiate a verification of the claimed location of the first device, wherein the location proof includes the captured DLI and a captured location.

Abstract: Fingerprinting, including: receiving a plurality of master datasets, each master dataset divided into a plurality of input segments, wherein at least one master dataset of said plurality of master datasets is uniquely marked; selecting a corresponding input segment from one of said plurality of master datasets; storing a segment identifier indicating from which master dataset said selected corresponding input segment was selected; and sending said selected corresponding input segment to a client computer system over a computer network.

Abstract: Generating an alternate reality game (ARG) using an augmented reality (AR) application, including: granting crypto-currency tokens to a player when the ARG is started by the player; enabling the player to find clues, discover objects, and interact with characters by presenting, to the player, a surrounding environment layered into a view of the AR application; determining whether the player has reached a decision point of a branching narrative; and enabling the player to send the crypto-currency tokens from the AR application to an intended destination when the decision point is reached.

Abstract: A method for enhancing color reproduction in an upscaling process, including: converting RGB-formatted data to color-space-separable-formatted data; sending the RGB-formatted data to a neural network for training to generate RGB-predicted data; converting the RGB-predicted data to color-space-separable-predicted data; computing a first loss function by calculating a first difference between the RGB-formatted data and the RGB-predicted data; extracting color-formatted data from the color-space-separable-formatted data; extracting color-predicted data from the color-space-separable-predicted data; computing a second loss function by calculating a second difference between the color-formatted data and the color-predicted data; and adjusting a balance between the first and second loss functions.

Abstract: Content distribution for one or more user devices, including: associating the one or more user devices with a user domain; acquiring content with one or more user accounts linked to the user domain; accessing the acquired content with the one or more user devices according to predetermined privileges, wherein access for an individual user device of the one or more user devices is valid while the individual user device is associated with the user domain and has an active status with the user domain.