Abstract: An exemplary computing device is configured to obtain a first set of control points used to generate a first panoramic image from a first locus point. The computing device is further configured to identify a second set of control points based upon which a second panoramic image is to be generated from a second locus point different from the first locus point. The identifying of the second set of control points is based on the first set of control points that were used to generate the first panoramic image from the first locus point. Based on the second set of control points, the computing device is also configured to generate the second panoramic image from the second locus point. Corresponding methods and systems are also disclosed.

Abstract: Embodiments described herein provide for the leveraging of edge-based resources (e.g., processing, memory, storage, and/or other resources of one or more Multi-Access/Mobile Edge Computing devices (“MECs”), such as MECs associated with a radio access network (“RAN”) of a wireless network) to process data from and/or provide instructions to microcontroller devices, System on Chip (“SoC”) devices, configurable logic boards, Internet of Things (“IoT”) devices, and/or other types of devices or systems. For example, embodiments described herein may provide for the creation and configuration of logical devices or systems based on one or more microcontrollers, SoC devices, etc., edge-based processing of sensor data and/or other types of data received or generated by the microcontrollers, SoC devices, etc., and the generation of instructions to control physical devices communicatively coupled to the microcontrollers, SoC devices, etc.

Abstract: Embodiments described herein provide for the leveraging of edge-based resources (e.g., processing, memory, storage, and/or other resources of one or more Multi-Access/Mobile Edge Computing devices (“MECs”), such as MECs associated with a radio access network (“RAN”) of a wireless network) to process data from and/or provide instructions to microcontroller devices, System on Chip (“SoC”) devices, configurable logic boards, Internet of Things (“IoT”) devices, and/or other types of devices or systems. For example, embodiments described herein may provide for the creation and configuration of logical devices or systems based on one or more microcontrollers, SoC devices, etc., edge-based processing of sensor data and/or other types of data received or generated by the microcontrollers, SoC devices, etc., and the generation of instructions to control physical devices communicatively coupled to the microcontrollers, SoC devices, etc.

Abstract: Embodiments described herein provide for the leveraging of edge-based resources (e.g., processing, memory, storage, and/or other resources of one or more Multi-Access/Mobile Edge Computing devices (“MECs”), such as MECs associated with a radio access network (“RAN”) of a wireless network) to process data from and/or provide instructions to microcontroller devices, System on Chip (“SoC”) devices, configurable logic boards, Internet of Things (“IoT”) devices, and/or other types of devices or systems. For example, embodiments described herein may provide for the creation and configuration of logical devices or systems based on one or more microcontrollers, SoC devices, etc., edge-based processing of sensor data and/or other types of data received or generated by the microcontrollers, SoC devices, etc., and the generation of instructions to control physical devices communicatively coupled to the microcontrollers, SoC devices, etc.

Abstract: Embodiments described herein provide for the leveraging of edge-based resources (e.g., processing, memory, storage, and/or other resources of one or more Multi-Access/Mobile Edge Computing devices (“MECs”), such as MECs associated with a radio access network (“RAN”) of a wireless network) to process data from and/or provide instructions to microcontroller devices, System on Chip (“SoC”) devices, configurable logic boards, Internet of Things (“IoT”) devices, and/or other types of devices or systems. For example, embodiments described herein may provide for the creation and configuration of logical devices or systems based on one or more microcontrollers, SoC devices, etc., edge-based processing of sensor data and/or other types of data received or generated by the microcontrollers, SoC devices, etc., and the generation of instructions to control physical devices communicatively coupled to the microcontrollers, SoC devices, etc.

Abstract: An exemplary computing device is configured to obtain a first set of control points used to generate a first panoramic image from a first locus point. The computing device is further configured to identify a second set of control points based upon which a second panoramic image is to be generated from a second locus point different from the first locus point. The identifying of the second set of control points is based on the first set of control points that were used to generate the first panoramic image from the first locus point. Based on the second set of control points, the computing device is also configured to generate the second panoramic image from the second locus point. Corresponding methods and systems are also disclosed.

Abstract: An exemplary image stitching recovery system detects a failed attempt by an image stitching system to generate a first panoramic image in a target location image set that includes a plurality of panoramic images each depicting a target location from a different respective locus point. The image stitching recovery system identifies a particular locus point at which a second panoramic image within the target location image set has been successfully generated, and identifies, based on a second set of control points that were used by the image stitching system to successfully generate the second panoramic image at the particular locus point, a first set of control points based upon which the first panoramic image is to be successfully generated. Subsequently, the image stitching recovery system directs the image stitching system to generate, based on the first set of control points, the first panoramic image in the target location image set.

Abstract: An exemplary depth capture system emits a first structured light pattern onto a surface of an object included in a real-world scene using a first structured light emitter included within the depth capture system. The depth capture system also emits, concurrently with the emitting of the first structured light pattern, a second structured light pattern onto the surface of the object using a second structured light emitter included within the depth capture system. The emitting of the second structured light pattern is different than the emitting of the first structured light pattern. The depth capture system detects the first and second structured light patterns using one or more optical sensors included within the depth capture system. Based on the detection of the structured light patterns, the depth capture system generates depth data representative of the surface of the object included in the real-world scene.

Abstract: An exemplary virtual reality media provider system differentiates static objects depicted in two-dimensional video data from dynamic objects depicted in the two-dimensional video data. Based on the differentiating of the static objects from the dynamic objects, the virtual reality media provider system generates dynamic volumetric models of the surfaces of the static objects and the dynamic objects. The virtual reality media provider system updates the dynamic volumetric models of the surfaces of the static objects with a lower regularity or on an as-needed basis, and the virtual reality media provider system separately updates the dynamic volumetric models of the surfaces of the dynamic objects with a higher regularity. The higher regularity is higher than the lower regularity and keeps the dynamic volumetric models of the surfaces of the dynamic objects up-to-date with what is occurring in the two-dimensional video data. Corresponding methods and systems are also disclosed.

Abstract: An exemplary virtual reality media provider system receives two-dimensional (“2D”) video data for surfaces of first and second objects located in a natural setting. The 2D video data is captured by first and second capture devices disposed at different positions with respect to the objects. The system distinguishes the first object from the second object by performing a plurality of techniques in combination with one another. The plurality of techniques include determining that the first object is moving in relation to the second object; and determining that, from a vantage point of at least one of the different positions, a representation of the first object captured within the 2D video data does not overlap with a representation of the second object. Based on the received 2D video data and the distinguishing of the first and second objects, the system generates an individually-manipulable volumetric model of the first object.

Abstract: An exemplary image stitching recovery system detects a failed attempt by an image stitching system to generate a first panoramic image in a target location image set that includes a plurality of panoramic images each depicting a target location from a different respective locus point. The image stitching recovery system identifies a particular locus point at which a second panoramic image within the target location image set has been successfully generated, and identifies, based on a second set of control points that were used by the image stitching system to successfully generate the second panoramic image at the particular locus point, a first set of control points based upon which the first panoramic image is to be successfully generated. Subsequently, the image stitching recovery system directs the image stitching system to generate, based on the first set of control points, the first panoramic image in the target location image set.

Abstract: An exemplary depth data generation system accesses first and second depth maps of a real-world scene, the depth maps independently captured using first and second depth map capture techniques, respectively. The first and second depth maps include, respectively, first and second depth data points both representative of a same physical point on a surface of an object in the real-world scene. Based on the first and second depth map capture techniques and based on an attribute of the surface of the object, the system assigns a first confidence value to the first depth data point and a second confidence value to the second depth data point. Based on the first and second confidence values, the system converges the first and second depth maps to form a converged depth map of the real-world scene that includes a third depth data point representing the physical point on the surface of the object.

Abstract: An exemplary virtual object presentation system accesses depth data for surfaces of a three-dimensional (“3D”) virtual object. The system determines, based on the depth data, a set of element configuration operations that, when performed by field formation elements included within an array of reconfigurable field formation elements, form a field in accordance with the depth data. Specifically, the field formed is to be haptically perceptible to a user using a field perception apparatus. The system may direct the field formation elements included within the array of reconfigurable field formation elements to perform the set of element configuration operations to thereby form the haptically perceptible field. In this way, the array of reconfigurable field formation elements generates a haptically perceptible virtual object representative of the 3D virtual object for perception by the user using the field perception apparatus. Corresponding methods are also disclosed.

Abstract: An augmented reality projection device includes an image sensor having a field of view into a real-world environment, a spatial sensor configured to detect a location and an orientation of the device in the environment, and a projector configured to project content onto a physical surface within the environment. The device determines the location and orientation of the device based on sensor output from the spatial sensor, and determines that a virtual target object is included within the field of view of the image sensor based on the determined location and orientation and based on a particular target object profile from a library of predetermined target object profiles. The device identifies content associated with the virtual target object and directs the projector to project the content onto the physical surface within the environment, the physical surface associated with the virtual target object. Corresponding methods and systems are also disclosed.

Abstract: A first communication device communicatively coupled with a second communication device by way of a first network interface and by way of a second network interface parallel to the first network interface prepares object data in accordance with a data partitioning protocol for transmission to the second communication device. The first communication device transmits the prepared object data to the second communication device at an overall data transfer rate that is at least as great as a sum of first and second data transfer rates associated, respectively, with the first and second network interfaces by concurrently transmitting first and second portions of the prepared object data by way of the first and second network interfaces and at the first and second data transfer rates, respectively. Corresponding methods and devices for receiving concurrently transmitted object data by way of parallel network interfaces are also disclosed.

Abstract: An augmented reality projection device includes an image sensor having a field of view into a real-world environment, a spatial sensor configured to detect a location and an orientation of the device in the environment, and a projector configured to project content onto a physical surface within the environment. The device determines the location and orientation of the device based on sensor output from the spatial sensor, and determines that a virtual target object is included within the field of view of the image sensor based on the determined location and orientation and based on a particular target object profile from a library of predetermined target object profiles. The device identifies content associated with the virtual target object and directs the projector to project the content onto the physical surface within the environment, the physical surface associated with the virtual target object. Corresponding methods and systems are also disclosed.

Abstract: An exemplary method includes a media player device (“device”) providing a user with an immersive virtual reality experience in accordance with a specification file corresponding to the immersive virtual reality experience. The specification file includes data that defines a plurality of elements included in the immersive virtual reality experience by providing a plurality of links for use by the device in acquiring the plurality of elements while providing the user with the immersive virtual reality experience. The method further includes the device detecting, while the immersive virtual reality experience is being provided to the user, real-world input associated with the user, and integrating the real-world input into the immersive virtual reality experience by updating the specification file to further include data that defines the real-world input as a user-specific element that is specific to the user and that is included in the immersive virtual reality experience.

Abstract: An augmented reality presentation system directs a sensor included within an augmented reality projection device to capture an image of a portion of a real-world environment included within a field of view of the sensor. As the sensor captures the image, the system determines that a target object located within the real-world environment is included within the field of view of the sensor, and identifies augmented reality content associated with the target object. As the sensor continues capturing the image, the system directs a projector included within the augmented reality projection device to project the augmented reality content onto a physical surface within the real-world environment and associated with the target object. The physical surface is physically detached from the augmented reality projection device and is included within the field of view of the sensor while the augmented reality content is projected onto the physical surface.

Abstract: An augmented reality presentation system directs a sensor included within an augmented reality projection device to capture an image of a portion of a real-world environment included within a field of view of the sensor. As the sensor captures the image, the system determines that a target object located within the real-world environment is included within the field of view of the sensor, and identifies augmented reality content associated with the target object. As the sensor continues capturing the image, the system directs a projector included within the augmented reality projection device to project the augmented reality content onto a physical surface within the real-world environment and associated with the target object. The physical surface is physically detached from the augmented reality projection device and is included within the field of view of the sensor while the augmented reality content is projected onto the physical surface.

Abstract: An exemplary depth data generation system accesses first and second depth maps of a real-world scene, the depth maps independently captured using first and second depth map capture techniques, respectively. The first and second depth maps include, respectively, first and second depth data points both representative of a same physical point on a surface of an object in the real-world scene. Based on the first and second depth map capture techniques and based on an attribute of the surface of the object, the system assigns a first confidence value to the first depth data point and a second confidence value to the second depth data point. Based on the first and second confidence values, the system converges the first and second depth maps to form a converged depth map of the real-world scene that includes a third depth data point representing the physical point on the surface of the object.