A method for determining experience quality of virtual reality (VR) multimedia includes, in a process of playing VR multimedia, obtaining a first sensory parameter, a second sensory parameter, and a third sensory parameter of the VR multimedia, where the first sensory parameter, the second sensory parameter, and the third sensory parameter are obtained by performing sampling separately according to at least two same perceptual dimensions, and are respectively parameters that affect fidelity experience, enjoyment experience, and interaction experience, and determining a mean opinion score (MOS) of the VR multimedia based on the first sensory parameter, the second sensory parameter, and the third sensory parameter of the VR multimedia. Because the third sensory parameter is a parameter that affects the interaction experience, an interaction feature of the VR multimedia is considered.

A system includes a mobile device having one or more cameras to take images; a sensor detecting reflected light from one or more lasers and a diffuser to detect object range or dimension; code for motion tracking, environmental understanding by detecting planes in an environment, and estimating light and dimensions of the surrounding based on the one or more lasers; code to estimate a three-dimensional (3D) volume of an object from multiple perspectives and from projected laser beams to measure size or scale and determine locations of points on the object's surface in a plane or a slice using time-of-flight, wherein positions and cross-sections for different slices are correlated to construct a 3D model of the object, including object position and shape; the device receiving user request to select a content from one or more augmented, virtual, or extended reality contents and rendering a reality view of the environment.

A method and system of creating a knowledge graph includes capturing information of a user interacting with given data, as user interaction data. The user interaction data is structured as a trail of actions over time. An ontology for a domain related to the user interaction data is received. Each action of the trail of actions is matched onto entities of the ontology. The knowledge graph is created based on the ontology having the matched actions.

A digital element located within a region near a device is identified. The digital element is located at a dynamically updated location. It is determined that the digital element is to be rendered. A representation of the digital element is generated in a rendered view of at least a portion of the region. Content of the digital element is provided upon receiving an indication that the digital element has been selected.

A computer-implemented method of providing virtual reality (VR) or Augmented Reality (AR) training includes adapting the VR/AR training based on feedback on the user's biometric data, which may include electroencephalogram (EEG) data and other biometric data. Associations are determined between the biometric data and psychological/neurological factors related to learning, such as a cognitive load, attention, anxiety, and motivation. In one implementation, predictive analytics are used to adapt the VR/AR training to maintain the user with an optimal learning zone during the training.

The present disclosure provides systems and methods for managing meeting notes. In accordance with some embodiments, a method is provided that includes receiving nonverbal cue information associated with one or more meeting participants, determining an engagement level for each of the one or more meeting participants based on emotional information associated with the nonverbal cue information, composing meeting notes based on the determined engagement level for each of the one or more meeting participants, and storing the meeting notes.

A computer architecture may comprise a processor, a memory, and a differential memory subsystem (DMS). A learning engine is stored on the memory and configured to present data to an expert user, to receive user sensory input measuring reactions related to the presented data, and to create an attention map based thereon. The attention map is indicative of portions of the presented data on which the expert user focused. The learning engine is configured to annotate the attention map with the natural language input labels and to train a neural network based on the user sensory input. The learning engine is configured to create a model based on the trained neural network, to provide an application program for an output target; and to instruct the output target via the application program to detect and remedy anomalous activity. The DMS is physically separate and configured for experimental data processing functions.

Commentary rating determination systems and methods determine a commentary rating for commentary about a subject media content event that has been generated by a community member. An exemplary embodiment receives video information acquired by a 360° video camera, identifies a physical object from the received video information, determines a physical attribute associated with the identified physical object, wherein the determined physical attribute describes a characteristic of the identified physical object, compares the determined physical attribute of the identified physical object with a plurality of predefined physical object attributes stored in a database, and in response to identifying one of the plurality of predefined physical object attributes that matches the determined physical attribute, associates the quality value of the identified one of the plurality of predefined physical object attributes with the identified physical object. Then, the commentary rating is determined for the commentary based on the associated quality value.

A virtual reality application adaptively generates a virtual reality experience intended to improve a user's mood. A plurality of digital assets is stored together with associated scores. A score for a digital asset represents a predicted amount of mood improvement occurring in a cohort of users having similar profiles to a target user in response to virtual reality experiences including the digital asset. A customized virtual reality experience is generated for the target user based at least in part of the user profile data on the scores. The user's change in mood is detected through survey and/or biometric data. Scores for the digital assets may then be updated in order to further learn their respective effects on the cohort of users.

A method for predicting a condition of living-being in an environment, the method including capturing image-data associated with the at-least one person and based thereupon determining a current-condition of the person; receiving content from a plurality of content-sources with respect to said at least one person being imaged, said content defined by at least one of text and statistics; defining one or more weighted parameters based on allocating a plurality of weights to at least one of the captured image data and the received content based on the current-condition; and predicting, by a predictive-analysis module, a condition of the at-least one person based on analysis of the one or more weighted parameters.