Abstract: There is provided a method including receiving a playback system identifier corresponding to a playback system, generating a blockchain corresponding to a content identifier identifying a content, wherein the blockchain is uniquely associated with the content identifier, establishing, in the blockchain, a block corresponding to the playback system identifier, sending an encrypted version of the content to the playback system, and in response to one or more updates to the blockchain by the playback system, providing a content encryption key to the playback system for decrypting the encrypted version of the content.

Abstract: A storytelling system includes location-based content (LBC) servers and LBC effects databases for use in a real-world story venue, and a computing platform communicatively coupled to those LBC servers and databases. A processor of the computing platform executes software code to receive story selection data from a user device, obtain a story template including story arcs each associated with one or more LBC effect(s) that corresponds to the story selection data, and determine, using a location of the user device, one of the story arcs as an active story arc. The software code also identifies an LBC interaction zone for the LBC effect(s), designates one LBC server and one LBC effects database for supporting the active story arc, and distributes one or more of the LBC effect(s) to the designated database. The designated server enables instantiation of the one or more of the LBC effect(s) at the LBC interaction zone.

Abstract: The present disclosure relates to calibration, customization, and improved user experiences for smart or bionic lenses that are worn by a user. The calibration techniques include detecting and correcting distortion of a display of the bionic lenses, as well as distortion due to characteristics of the lens or eyes of the user. The customization techniques include utilizing the bionic lenses to detect eye characteristics that can be used to improve insertion of the bionic lenses, track health over time, and provide user alerts. The user experiences include interactive environments and animation techniques that are improved via the bionic lenses.

Abstract: There is provided a method for use by a mobile device. The method includes launching a software application requiring an identity verification of each of a plurality of users for performing a requested action, the plurality of users including a first user and a second user, receiving a first biometric information of the first user and a second biometric information of the second user, sending the first biometric information of the first user and the second biometric information of the second user to a server, receiving notifications from the server as to whether the first and second biometric information corresponding to biometric information in first user and second user profiles, respectively, and performing the requested action, if the notifications indicate a match.

Abstract: A system for performing digital rights protected content playing includes a computing platform having a hardware processor and a memory storing a software code. The hardware processor executes the software code to receive, from a first user, metadata identifying one or more content segment(s), determine whether the first user has a right to access the content segment(s), produce a playlist using the metadata when the first user has the right, and output the playlist to the first user and/or a second user. The hardware processor may further execute the software code to receive the playlist from the second user, determine each content segment identified by the playlist that the second user has a right to access, generate a content compilation that omits any content segment identified by the playlist to which the second user lacks the right, and playout the content compilation to the second user.

Abstract: A system includes a computing platform having a hardware processor and a memory storing a software code and a neural network (NN) having multiple layers including a last activation layer and a loss layer. The hardware processor executes the software code to identify different combinations of layers for testing the NN, each combination including candidate function(s) for the last activation layer and candidate function(s) for the loss layer. For each different combination, the software code configures the NN based on the combination, inputs, into the configured NN, a training dataset including multiple data objects, receives, from the configured NN, a classification of the data objects, and generates a performance assessment for the combination based on the classification. The software code determines a preferred combination of layers for the NN including selected candidate functions for the last activation layer and the loss layer, based on a comparison of the performance assessments.

Abstract: In various embodiments, a training application generates training items for three-dimensional (3D) pose estimation. The training application generates multiple posed 3D models based on multiple 3D poses and a 3D model of a person wearing a costume that is associated with multiple visual attributes. For each posed 3D model, the training application performs rendering operation(s) to generate synthetic image(s). For each synthetic image, the training application generates a training item based on the synthetic image and the 3D pose associated with the posed 3D model from which the synthetic image was rendered. The synthetic images are included in a synthetic training dataset that is tailored for training a machine-learning model to compute estimated 3D poses of persons from two-dimensional (2D) input images. Advantageously, the synthetic training dataset can be used to train the machine-learning model to accurately infer the orientations of persons across a wide range of environments.

Abstract: In some implementations, a device may provide a data structure storing first data, wherein the first data indirectly identifies second data, and wherein the second data identifies a particular individual. The device may obtain, from the data structure, the first data. The device may generate a cryptographically random value using a secure generator. The device may combine the first data and the cryptographically random value to generate hashing input data. The device may perform, using a hashing algorithm, a hashing operation on the hashing input data to generate de-identified first data, wherein re-identification of the de-identified first data requires knowledge of at least the first data, the cryptographically random value, and the de-identified first data. The device may perform an action using the de-identified first data.

Abstract: This disclosure relates to systems and methods for using augmented reality with the internet of things. An augmented reality experience may be provided based on an operation of an object. Operation status information of a detected object may be obtained and a visual effect may be determined based on the operation status information. An object may be controlled using augmented reality. Operation status information of a detected object may be obtained and a control option may be determined based on the operation status information. A visual effect may be determined based on the control option and a user input regarding the control option may be obtained. A control information configured to effectuate a change in the operation of the object may be transmitted to the object.

Abstract: Techniques for using holographic imagery for eyeline reference for performers. A first computer generated object is identified for display to a first performer at a designated physical position on a set. A first holographic projection of the first computer generated object is generated using a first holographic display. The first holographic display is configured to make the first holographic projection appear, to the first performer, to be located at the designated physical position on the set. One or more images of the performer are captured using an image capture device with a field of view that encompasses both the first performer and the designated physical position on the set. The captured one or more images depict the first performer and do not depict the first holographic projection. The first computer generated object is added to the captured one or more images after the capturing.

Abstract: Restoration methods and systems are disclosed for video remastering. Techniques disclosed include receiving a video sequence. For each frame of the video sequence, techniques disclosed include encoding, by a degradation encoder, a video content associated with the frame into a latent vector. The latent vector is a representation of the degradation present in the video content; the degradation present in the video content includes one or more degradation types. Based on the latent vector and the video content, techniques disclosed further include generating, by a backbone network, one or more feature maps, and, then, restoring the frame based on the one or more feature maps.

Abstract: A system for performing synergistic object tracking and pattern recognition for event representation includes a computing platform having processing hardware and a system memory storing a software code. The processing hardware is configured to execute the software code to receive event data corresponding to one or more propertie(s) of an object, to generate, using the event data, a location data estimating a location of each of multiple predetermined landmarks of the object, and to predict, using one or both of the event data and the location data, a pattern corresponding to the propertie(s) of the object. The processing hardware is further configured to execute the software code to update, using the predicted pattern, the location data, and to merge the updated location data and the predicted pattern to provide merged data.

Abstract: Techniques are disclosed for creating digital faces. In some examples, an anatomical face model is generated from a data set including captured facial geometries of different individuals and associated bone geometries. A model generator segments each of the captured facial geometries into patches, compresses the segmented geometry associated with each patch to determine local deformation subspaces of the anatomical face model, and determines corresponding compressed anatomical subspaces of the anatomical face model. A sculpting application determines, based on sculpting input from a user, constraints for an optimization to determine parameter values associated with the anatomical face model. The parameter values can be used, along with the anatomical face model, to generate facial geometry that reflects the sculpting input.

Abstract: Techniques for machine learning optimization are provided. A video comprising a plurality of segments is received, and a first segment of the plurality of segments is processed with a machine learning (ML) model to generate a plurality of tags, where each of the plurality of tags indicates presence of an element in the first segment. A respective accuracy value is determined for each respective tag of the plurality of tags, where the respective accuracy value is based at least in part on a maturity score for the ML model. The first segment is classified as accurate, based on determining that an aggregate accuracy of tags corresponding to the first segment exceeds a predefined threshold. Upon classifying the first segment as accurate, the first segment is bypassed during a review process.

Abstract: Various embodiments set forth systems and techniques for training a landmark model. The techniques include determining, using the landmark model, a first landmark in a set of first landmarks associated with a first image; performing, on the first image, a first perturbation to obtain a second image; determining, using the landmark model, a second landmark in a set of second landmarks associated with the second image; determining, based on a first distance between the first landmark and the second landmark, a first loss function; and updating, based on the first loss function, a first parameter of the landmark model.

Abstract: There is provided a method for use by a playback system to play back encrypted content associated with a first globally unique identifier (ID). The method includes storing an encrypted content in a memory being under control of a memory controller having a second globally unique ID, storing the first globally unique ID, transmitting a request from the memory controller to a license server, the request comprising the first globally unique ID, the second globally unique ID and a request for a content license to play back the encrypted content, receiving the content license enabling a right for the playback of the encrypted content, the content license including content keys and being encrypted to be decryptable according to a memory controller secret associated with the second globally unique ID, decrypting the content license, according to the memory controller secret to recover the content keys to a playback module.

Abstract: A virtual puppeteering system includes a portable device including a camera, a display, a hardware processor, and a system memory storing an object animation software code. The hardware processor is configured to execute the object animation software code to, using the camera, generate an image in response to receiving an activation input, using the display, display the image, and receive a selection input selecting an object shown in the image. The hardware processor is further configured to execute the object animation software code to determine a distance separating the selected object from the portable device, receive an animation input, identify, based on the selected object and the received animation input, a movement for animating the selected object, generate an animation of the selected object using the determined distance and the identified movement, and render the animation of the selected object.

Abstract: Methods for improving operation of a user device executing an application. The methods include collecting a first set of data corresponding to a run time environment of the application, collecting a second set of data corresponding to a crash of the application, identifying a cause of the crash based on the first set of data and a second set of data and determining the cause of the crash is associated with an application feature corresponding to a feature flag.

Abstract: Techniques for buffering data over high bandwidth networks are provided. A first portion of data is downloaded into a buffer at a first download speed via a first network. The first portion of data is outputted from the buffer. Upon determining that data is being downloaded, via a second network, at a second download speed greater than the first download speed, a size of the buffer is expanded, and a second portion of data is downloaded into the expanded buffer.