Abstract: Features described herein generally relate to providing spatiotemporal guidance within a 360-degree video. Particularly, while a 360-degree video is being displayed to a user, a current location of the view of the user within the 360-degree video is determined. Additionally, regions of interest may be identified within the 360-degree video, along with their location and a time in which the regions of interest are active within the 360-degree video. A visual guide is then overlaid onto the 360-degree video that indicates a current location of the view of the user, as well as locations of one or more regions of interest, as well as the time during which each region of interest is active (able to be viewed) within the 360-degree video. By viewing the visual guide, the user may be able to anticipate a location and timing of regions of interest within the 360-degree video and adjust their gaze to the correct location at the correct time to view such regions of interest.

Abstract: Techniques are for analyzing contextual clues from an extended reality environment and, based on the analysis of the contextual clues, intuitively superimposing and integrating customized digital information into the artificial reality environment via a virtual assistant to recommend and lead the user into suggested action. A method includes obtaining input data from a user, generating a graph of objects, attributes, and relationships between objects extracted from the input data, determining one or more interactions to be presented, initiated, or executed based on the graph and a profile associated with the user, determining virtual content data to be used for rendering virtual content based on the one or more interactions, and rendering the virtual content in an extended reality environment displayed to the user based on the virtual content data. The virtual content is used to present, initiate, or execute the one or more interactions for the user.

Abstract: A non-transitory, computer-readable storage medium includes instructions to be executed at an extended-reality (XR) headset is described herein. The instructions cause the XR headset to present, via the XR headset worn by a first user, a three-dimensional volumetric representation of an area of space within an XR application that was selected to be collaboratively edited by the first user and a second user. The three-dimensional volumetric representation of the area of space is viewable by the second user. The instructions further cause the XR headset to receive an indication that the second user has provided an input to add an XR object to the area of space. The instructions further cause the XR headset to, in response to receiving the indication, update the three-dimensional volumetric representation to include the area of space with the XR object.

Abstract: Features described herein generally relate to providing spatiotemporal guidance within a 360-degree video. Particularly, while a 360-degree video is being displayed to a user, a current location of the view of the user within the 360-degree video is determined. Additionally, regions of interest may be identified within the 360-degree video, along with their location and a time in which the regions of interest are active within the 360-degree video. A visual guide is then overlaid onto the 360-degree video that indicates a current location of the view of the user, as well as locations of one or more regions of interest, as well as the time during which each region of interest is active (able to be viewed) within the 360-degree video. By viewing the visual guide, the user may be able to anticipate a location and timing of regions of interest within the 360-degree video and adjust their gaze to the correct location at the correct time to view such regions of interest.

Abstract: Techniques for analyzing contextual clues from an extended reality environment and, based on the analysis of the contextual clues, intuitively superimposing and integrating customized digital information into the artificial reality environment via a virtual assistant to recommend and lead the user into suggested action. In one particular aspect, a computer-implements method is provided that includes obtaining input data from a user, generating a graph of objects, attributes, and relationships between objects extracted from the input data, determining one or more interactions to be presented, initiated, or executed based on the graph and a profile associated with the user, determining virtual content data to be used for rendering virtual content based on the one or more interactions, and rendering the virtual content in an extended reality environment displayed to the user based on the virtual content data. The virtual content is used to present, initiate, or execute the one or more interactions for the user.

Abstract: An electronic device tracks, for a user performing a target acquisition movement within a 3D space, movement parameters of a plurality of input devices of the user. The electronic device predicts, for the user, a region of interest within the 3D space, based on the movement parameters. The region of interest includes a plurality of targets in close proximity. The electronic device predicts an endpoint of the target acquisition movement, within the region of interest. In some embodiments, the plurality of input devices includes an eye tracking input device, each input device corresponds to a predefined input device type, and the movement parameters include gaze data from the eye tracking input device. In some embodiments, input devices includes an eye tracking input device, a head-mounted display, and a hand-held controller, and the user's eye, hand, and head movements are coordinated.

Abstract: An electronic device tracks, for a user performing a target acquisition movement within a 3D space, movement parameters of a plurality of input devices of the user. The electronic device predicts, for the user, a region of interest within the 3D space, based on the movement parameters. The region of interest includes a plurality of targets in close proximity. The electronic device predicts an endpoint of the target acquisition movement, within the region of interest. In some embodiments, the plurality of input devices includes an eye tracking input device, each input device corresponds to a predefined input device type, and the movement parameters include gaze data from the eye tracking input device. In some embodiments, input devices includes an eye tracking input device, a head-mounted display, and a hand-held controller, and the user's eye, hand, and head movements are coordinated.

Abstract: An electronic device tracks, for a user performing a target acquisition movement within a 3D space, movement parameters of a plurality of input devices of the user. The electronic device predicts, for the user, a region of interest within the 3D space, using a regression model, based on the movement parameters. The region of interest includes a plurality of targets in close proximity. The electronic device predicts an endpoint of the target acquisition movement, within the region of interest, using a pointer facilitation technique. In some embodiments, the plurality of input devices includes an eye tracking input device, each input device corresponds to a predefined input device type, and the movement parameters include gaze data from the eye tracking input device. In some embodiments, input devices includes an eye tracking input device, a head-mounted display, and a hand-held controller, and the user's eye, hand, and head movements are coordinated.

Abstract: An electronic device tracks, for a user performing a target acquisition movement within a 3D space, movement parameters of a plurality of input devices of the user. The electronic device predicts, for the user, a region of interest within the 3D space, using a regression model, based on the movement parameters. The region of interest includes a plurality of targets in close proximity. The electronic device predicts an endpoint of the target acquisition movement, within the region of interest, using a pointer facilitation technique. In some embodiments, the plurality of input devices includes an eye tracking input device, each input device corresponds to a predefined input device type, and the movement parameters include gaze data from the eye tracking input device. In some embodiments, input devices includes an eye tracking input device, a head-mounted display, and a hand-held controller, and the user's eye, hand, and head movements are coordinated.

Abstract: An electronic device with a display selects a subset of templates from a library of templates. Each of the templates comprises logged movements of one or more predefined input device types in a 3D space and each template includes one or more movement parameters. The electronic device tracks, for a user, movement parameters of at least one input device of the user. The at least one input device corresponds to one of the predefined input device types. The electronic device compares the tracked movement parameters of the at least one input device of the user to the movement parameters for the subset of the templates selected from the library of templates. The electronic device predicts, based on the comparison, a goal target ray, within the 3D space. In some embodiments, the goal target ray is highlighted or visually emphasized according to the prediction.