Abstract: An exemplary method includes maintaining a receiver-side mesh-vertices list, receiving duplicative-vertex information from a sender, and responsively reducing the receiver-side mesh-vertices list in accordance with the received duplicative-vertex information, and rendering, using the reduced receiver-side mesh-vertices list, viewpoint-adaptive three-dimensional (3D) personas of a subject at least in part by weighting video pixel colors from different video-camera vantage points of video cameras that capture video streams of the subject, the weighting being performed according to a respective geometric relationship of each video-camera vantage point to a user-selected viewpoint.

Abstract: An exemplary method includes generating a 3D mesh of a subject based on frames of time-synchronized video streams of a subject, the frames associated with a first time and generating a transformed facial-mesh model based on a facial portion of the 3D mesh and a facial-mesh model. The method further includes generating a hybrid mesh by combining the transformed facial-mesh model and at least a portion of the 3D mesh. The method further includes generating a current 3D mesh based on frames of the time-synchronized video streams associated with a second time that temporally follows the first time. The method further includes generating a deformed historical 3D mesh by applying a non-rigid deformation process to the hybrid mesh based on the current 3D mesh. The method further includes compressing the deformed historical 3D mesh to form at least one triangle-based 3D submesh including a plurality of submesh triangles.

Abstract: An illustrative method includes obtaining a three-dimensional (3D) mesh of a subject, obtaining a mesh model, and generating a hybrid mesh of the subject. The generating includes replacing a portion of the 3D mesh with the mesh model such that the hybrid mesh includes a non-replaced portion of the 3D mesh represented at a first resolution and the mesh model representing the replaced portion of the 3D mesh at a second resolution.

Abstract: An illustrative volumetric capture system accesses a machine learning model associated with bodies of a particular body type, as well as a two-dimensional (2D) image captured by a capture device located at a real-world scene. The 2D image depicts a body of the particular body type that is present at the real-world scene. Using the machine learning model and based on the 2D image, the volumetric capture system identifies a 2D joint location, from a perspective of the capture device, of a particular joint of the body. The volumetric capture system also generates a three-dimensional (3D) reference model of the body that represents the particular joint of the body at a 3D joint location that is determined based on the 2D joint location identified using the machine learning model. Corresponding methods and systems are also disclosed.

Abstract: An exemplary three-dimensional (3D) simulation system accesses a two-dimensional (2D) video image captured by a video capture device and that depicts a bounded real-world scene and a real-world object present within the bounded real-world scene. The 3D simulation system accesses respective 3D models of the bounded real-world scene and the real-world object. Based on the 2D video image, the 3D simulation system tracks a spatial characteristic of the real-world object relative to the bounded real-world scene. Based on the tracked spatial characteristic of the real-world object and the 3D models of the bounded real-world scene and the real-world object, the 3D simulation system generates a 3D simulation of the bounded real-world scene within which the real-world object is simulated in accordance with the tracked spatial characteristic of the real-world object. Corresponding methods and systems are also disclosed.

Abstract: A method includes receiving two-dimensional video streams from a plurality of cameras, the two-dimensional video streams including multiple angles of a sporting event. The method further includes determining boundaries of the sporting event from the two-dimensional video streams. The method further includes identifying a location of a sporting object during the sporting event. The method further includes identifying one or more players in the sporting event. The method further includes identifying poses of each of the one or more players during the sporting event. The method further includes generating a three-dimensional model of the sporting event based on the boundaries of the sporting event, the location of the sporting object during the sporting event, and the poses of each of the one or more players during the sporting event. The method further includes generating a simulation of the three-dimensional model.

Abstract: Systems and methods relate to receiving a plurality of video streams captured of a subject by a plurality of video cameras, each video stream including video frames time-synchronized according to a shared frame rate, each video camera having a known vantage point in a predetermined coordinate system; obtaining at least one three-dimensional (3D) mesh of the subject at the shared frame rate, the 3D mesh time-synchronized with the video frames of the video streams, the at least one mesh including a plurality of vertices with known locations in the predetermined coordinate system; calculating one or more lists of visible-vertices at the shared frame rate, each list including a subset of the plurality of vertices of the at least one 3D mesh of the subject, the subset being a function of the location of the known vantage point associated with at least one of the plurality of video cameras; generating one or more time-synchronized data streams at the shared frame rate, the one or more time-synchronized data streams

Abstract: An exemplary method includes maintaining a receiver-side mesh-vertices list, receiving duplicative-vertex information from a sender, and responsively reducing the receiver-side mesh-vertices list in accordance with the received duplicative-vertex information, and rendering, using the reduced receiver-side mesh-vertices list, viewpoint-adaptive three-dimensional (3D) personas of a subject at least in part by weighting video pixel colors from different video-camera vantage points of video cameras that capture video streams of the subject, the weighting being performed according to a respective geometric relationship of each video-camera vantage point to a user-selected viewpoint.

Abstract: An illustrative method includes obtaining a three-dimensional (3D) mesh of a subject, obtaining a mesh model, and generating a hybrid mesh of the subject. The generating includes replacing a portion of the 3D mesh with the mesh model such that the hybrid mesh includes a non-replaced portion of the 3D mesh represented at a first resolution and the mesh model representing the replaced portion of the 3D mesh at a second resolution.

Abstract: Systems and methods relate to encoded video streams including geometric-data streams transmitted to a receiver for rendering of a viewpoint-adaptive 3D persona. A method includes obtaining at least one triangle-based three-dimensional (3D) submesh of a subject, wherein the obtained triangle-based 3D submesh includes a plurality of submesh vertices that define a plurality of submesh triangles, identifying a plurality of strips of the submesh triangles, generating triangle-strip data representing the identified strips of submesh triangles, generating compressed-submesh data that includes the triangle-strip data, and transmitting the compressed-submesh data to a receiver for reconstruction of the triangle-based 3D submesh of the subject.

Abstract: Systems and methods relate to receiving a plurality of video streams captured of a subject by a plurality of video cameras, each video stream including video frames time-synchronized according to a shared frame rate, each video camera having a known vantage point in a predetermined coordinate system; obtaining at least one three-dimensional (3D) mesh of the subject at the shared frame rate, the 3D mesh time-synchronized with the video frames of the video streams, the at least one mesh including a plurality of vertices with known locations in the predetermined coordinate system; calculating one or more lists of visible-vertices at the shared frame rate, each list including a subset of the plurality of vertices of the at least one 3D mesh of the subject, the subset being a function of the location of the known vantage point associated with at least one of the plurality of video cameras; generating one or more time-synchronized data streams at the shared frame rate, the one or more time-synchronized data streams

Abstract: Systems and methods relate receiving video streams captured of a subject by video cameras, each video stream including video frames that are time-synchronized with the video, each video camera having a known vantage point in a predetermined coordinate system; obtaining at least one three-dimensional (3D) mesh of the subject, the mesh being time-synchronized and including a plurality of mesh vertices with known locations; identifying a user-selected viewpoint, and identifying a viewpoint-specific subset of the mesh vertices visible; generating 3D submeshes of the subject by calculating visible-vertices lists from the vantage point of each video camera from which the viewpoint-specific subset of mesh vertices is visible; projecting mesh vertices from the calculated visible-vertices lists on to video pixels; and rendering viewpoint-adaptive 3D personas of the subject by weighting video pixel colors from different video-camera vantage points according to the geometric relationship of each video-camera vantage poi

Abstract: Systems and methods relate to encoded video streams including geometric-data streams transmitted to a receiver for rendering of a viewpoint-adaptive 3D persona. A method includes obtaining a three-dimensional (3D) mesh of a subject generated from depth-camera-captured information about the subject, obtaining a facial-mesh model, locating a facial portion of the obtained 3D mesh of the subject, computing a geometric transform based on the facial portion and the facial-mesh model, the geometric transform determined in response to one or more aggregated error differences between a plurality of feature points on the facial-mesh model and a plurality of corresponding feature points on the facial portion of the obtained 3D mesh, generating a transformed facial-mesh model using the geometric transform and generating a hybrid mesh of the subject at least in part by combining the transformed facial-mesh model and at least a portion of the obtained 3D mesh.

Abstract: Illustrative systems and methods for determining and using three-dimensional (3D) meshes of a subject are described herein. An illustrative system obtains 3D meshes of a subject at a frame rate, the 3D meshes including a current-frame 3D mesh corresponding to a current frame and a previous-frame 3D mesh corresponding to a previous frame. The system deforms the previous-frame 3D mesh based on the current-frame 3D mesh and determines, based on the deformed previous-frame 3D mesh, a 3D mesh of the subject for use with the current frame. In certain examples, the system uses the 3D mesh of the subject to facilitate rendering of a viewpoint-adaptive 3D representation of the subject.

Abstract: An exemplary method includes generating a 3D mesh of a subject based on frames of time-synchronized video streams of a subject, the frames associated with a first time and generating a transformed facial-mesh model based on a facial portion of the 3D mesh and a facial-mesh model. The method further includes generating a hybrid mesh by combining the transformed facial-mesh model and at least a portion of the 3D mesh. The method further includes generating a current 3D mesh based on frames of the time-synchronized video streams associated with a second time that temporally follows the first time. The method further includes generating a deformed historical 3D mesh by applying a non-rigid deformation process to the hybrid mesh based on the current 3D mesh. The method further includes compressing the deformed historical 3D mesh to form at least one triangle-based 3D submesh including a plurality of submesh triangles.

Abstract: Systems and methods relate to receiving a plurality of video streams captured of a subject by a plurality of video cameras, each video stream including video frames time-synchronized according to a shared frame rate, each video camera having a known vantage point in a predetermined coordinate system; obtaining at least one three-dimensional (3D) mesh of the subject at the shared frame rate, the 3D mesh time-synchronized with the video frames of the video streams, the at least one mesh including a plurality of vertices with known locations in the predetermined coordinate system; calculating one or more lists of visible-vertices at the shared frame rate, each list including a subset of the plurality of vertices of the at least one 3D mesh of the subject, the subset being a function of the location of the known vantage point associated with at least one of the plurality of video cameras; generating one or more time-synchronized data streams at the shared frame rate, the one or more time-synchronized data streams

Abstract: An illustrative volumetric capture system accesses a machine learning model associated with bodies of a particular body type, as well as a two-dimensional (2D) image captured by a capture device located at a real-world scene. The 2D image depicts a body of the particular body type that is present at the real-world scene. Using the machine learning model and based on the 2D image, the volumetric capture system identifies a 2D joint location, from a perspective of the capture device, of a particular joint of the body. The volumetric capture system also generates a three-dimensional (3D) reference model of the body that represents the particular joint of the body at a 3D joint location that is determined based on the 2D joint location identified using the machine learning model. Corresponding methods and systems are also disclosed.

Abstract: An exemplary three-dimensional (3D) simulation system accesses a two-dimensional (2D) video image captured by a video capture device and that depicts a bounded real-world scene and a real-world object present within the bounded real-world scene. The 3D simulation system accesses respective 3D models of the bounded real-world scene and the real-world object. Based on the 2D video image, the 3D simulation system tracks a spatial characteristic of the real-world object relative to the bounded real-world scene. Based on the tracked spatial characteristic of the real-world object and the 3D models of the bounded real-world scene and the real-world object, the 3D simulation system generates a 3D simulation of the bounded real-world scene within which the real-world object is simulated in accordance with the tracked spatial characteristic of the real-world object. Corresponding methods and systems are also disclosed.

Abstract: Systems and methods relate to encoded video streams including geometric-data streams transmitted to a receiver for rendering of a viewpoint-adaptive 3D persona. A method includes obtaining a three-dimensional (3D) mesh of a subject generated from depth-camera-captured information about the subject, obtaining a facial-mesh model, locating a facial portion of the obtained 3D mesh of the subject, computing a geometric transform based on the facial portion and the facial-mesh model, the geometric transform determined in response to one or more aggregated error differences between a plurality of feature points on the facial-mesh model and a plurality of corresponding feature points on the facial portion of the obtained 3D mesh, generating a transformed facial-mesh model using the geometric transform and generating a hybrid mesh of the subject at least in part by combining the transformed facial-mesh model and at least a portion of the obtained 3D mesh.

Abstract: Systems and methods relate to encoded video streams including geometric-data streams transmitted to a receiver for rendering of a viewpoint-adaptive 3D persona. A method includes obtaining a three-dimensional (3D) mesh of a subject generated from depth-camera-captured information about the subject, obtaining a facial-mesh model, locating a facial portion of the obtained 3D mesh of the subject, computing a geometric transform based on the facial portion and the facial-mesh model, the geometric transform determined in response to one or more aggregated error differences between a plurality of feature points on the facial-mesh model and a plurality of corresponding feature points on the facial portion of the obtained 3D mesh, generating a transformed facial-mesh model using the geometric transform and generating a hybrid mesh of the subject at least in part by combining the transformed facial-mesh model and at least a portion of the obtained 3D mesh.