Abstract: A digital human interactive platform can determine a contextual response to a user input and generate a digital human. The digital human can convey the contextual response to the user in real time. The digital human can be configured to convey the contextual response with a predetermined behavior corresponding to the contextual response.

Abstract: A digital human development platform can enable a user to generate a digital human. The digital human development platform can receive user input specifying a dialogue for the digital human and one or more behaviors for the digital human, the one or more specified behaviors corresponding with one or more portions of the dialog on a common timeline. Scene data can be generated with the digital human development platform by merging the one or more behaviors with one or more portions of the dialogue based on times of the one or more behaviors and the one or more portions of the dialog on the common timeline.

Abstract: In one embodiment, a method includes, by one or more computing systems: receiving one or more non-video inputs, where the one or more non-video inputs include at least one of a text input, an audio input, or an expression input, accessing a K-NN graph including several sets of nodes, where each set of nodes corresponds to a particular semantic context out of several semantic contexts, determining one or more actions to be performed by a digital avatar based on the one or more identified semantic contexts, generating, in real-time in response to receiving the one or more non-video inputs and based on the determined one or more actions, a video output of the digital avatar including one or more human characteristics corresponding to the one or more identified semantic contexts, and sending, to a client device, instructions to present the video output of the digital avatar.

Abstract: A digital human interactive platform can determine a contextual response to a user input and generate a digital human. The digital human can convey the contextual response to the user in real time. The digital human can be configured to convey the contextual response with a predetermined behavior corresponding to the contextual response.

Abstract: A digital human development platform can enable a user to generate a digital human. The digital human development platform can receive user input specifying a dialogue for the digital human and one or more behaviors for the digital human, the one or more specified behaviors corresponding with one or more portions of the dialog on a common timeline. Scene data can be generated with the digital human development platform by merging the one or more behaviors with one or more portions of the dialogue based on times of the one or more behaviors and the one or more portions of the dialog on the common timeline.

Abstract: Communications pertaining to a digital human can include communicating via a lighting system based on determining an aspect of a user based on one or more sensor-generated signals. A communicative lighting sequence can be determined based on the user attribute. The lighting sequence can correspond to a condition of a digital human and can be configured to communicate to the user the condition of the digital human. The light sequence can be generated with an LED array mounted on a digital human display assembly.

Abstract: A digital human display assembly can include a rectangular display panel enclosed within a frame, the rectangular display panel capable of visually rendering a digital human during an interactive dialogue between the digital human and a user. The digital human display assembly also can include a glass covering enclosed within the frame and extending over a front side of the rectangular display panel. A base can support the frame in an upright position. A light emitting diode (LED) arrangement can be positioned on one or more outer portions of the frame.

Abstract: In one embodiment, a method includes, by one or more computing systems: receiving one or more non-video inputs, where the one or more non-video inputs include at least one of a text input, an audio input, or an expression input, accessing a K-NN graph including several sets of nodes, where each set of nodes corresponds to a particular semantic context out of several semantic contexts, determining one or more actions to be performed by a digital avatar based on the one or more identified semantic contexts, generating, in real-time in response to receiving the one or more non-video inputs and based on the determined one or more actions, a video output of the digital avatar including one or more human characteristics corresponding to the one or more identified semantic contexts, and sending, to a client device, instructions to present the video output of the digital avatar.

Abstract: A system for determining and tracking camera pose includes a dynamic vision sensor (DVS) configured to generate a current DVS image, an inertial measurement unit (IMU) configured to generate inertial data, and a memory. The memory is configured to store a 3-dimensional (3D) map of a known 3D environment. The system may also include a processor coupled to the memory. The processor is configured to initiate operations including determining a current camera pose for the DVS based on the current DVS image, the inertial data, the 3D map, and a prior camera pose.

Abstract: A method of camera pose and plane estimation may include detecting a marker within a 3-dimensional (3D) environment by detecting, using a Dynamic Vision Sensor (DVS), a first plurality of light sources arranged in a known shape and blinking at a first frequency, wherein the known shape corresponds to the marker, determining an orientation and an identity of the marker based upon detecting, using the DVS, a second plurality of light sources corresponding to the marker and blinking at a second frequency different from the first frequency. A camera pose for the DVS may be determined based upon the known shape, the orientation, and the identity of the marker using the processor.

Abstract: Monitoring health status of a user may be performed by an apparatus that includes a sensor adapted to generate sensor data, a memory adapted to store a plurality of baseline biological markers for a user, wherein the plurality of baseline biological markers include respiratory rhythm, and a processor coupled to the memory and the sensor. The processor is adapted to, in response to detecting that the user is performing physical activity, determine a biological marker from the sensor data. The processor is adapted to compare the biological marker with the baseline biological marker. The processor is further adapted to, in response to detecting a change in the biological marker, provide a notification indicating a change in health status.

Abstract: A method of camera pose and plane estimation may include detecting a marker within a 3-dimensional (3D) environment by detecting, using a Dynamic Vision Sensor (DVS), a first plurality of light sources arranged in a known shape and blinking at a first frequency, wherein the known shape corresponds to the marker, determining an orientation and an identity of the marker based upon detecting, using the DVS, a second plurality of light sources corresponding to the marker and blinking at a second frequency different from the first frequency. A camera pose for the DVS may be determined based upon the known shape, the orientation, and the identity of the marker using the processor.

Abstract: A system for determining and tracking camera pose includes a dynamic vision sensor (DVS) configured to generate a current DVS image, an inertial measurement unit (IMU) configured to generate inertial data, and a memory. The memory is configured to store a 3-dimensional (3D) map of a known 3D environment. The system may also include a processor coupled to the memory. The processor is configured to initiate operations including determining a current camera pose for the DVS based on the current DVS image, the inertial data, the 3D map, and a prior camera pose.