Abstract: Some implementations of the disclosure are directed to techniques for facial reconstruction from a sparse set of facial markers. In one implementation, a method comprises: obtaining data comprising a captured facial performance of a subject with a plurality of facial markers; determining a three-dimensional (3D) bundle corresponding to each of the plurality of facial markers of the captured facial performance; using at least the determined 3D bundles to retrieve, from a facial dataset comprising a plurality of facial shapes of the subject, a local geometric shape corresponding to each of the plurality of the facial markers; and merging the retrieved local geometric shapes to create a facial reconstruction of the subject for the captured facial performance.

Abstract: Some implementations of the disclosure are directed to techniques for facial reconstruction from a sparse set of facial markers. In one implementation, a method comprises: obtaining data comprising a captured facial performance of a subject with a plurality of facial markers; determining a three-dimensional (3D) bundle corresponding to each of the plurality of facial markers of the captured facial performance; using at least the determined 3D bundles to retrieve, from a facial dataset comprising a plurality of facial shapes of the subject, a local geometric shape corresponding to each of the plurality of the facial markers; and merging the retrieved local geometric shapes to create a facial reconstruction of the subject for the captured facial performance.

Abstract: Some implementations of the disclosure are directed to techniques for facial reconstruction from a sparse set of facial markers. In one implementation, a method comprises: obtaining data comprising a captured facial performance of a subject with a plurality of facial markers; determining a three-dimensional (3D) bundle corresponding to each of the plurality of facial markers of the captured facial performance; using at least the determined 3D bundles to retrieve, from a facial dataset comprising a plurality of facial shapes of the subject, a local geometric shape corresponding to each of the plurality of the facial markers; and merging the retrieved local geometric shapes to create a facial reconstruction of the subject for the captured facial performance.

Abstract: A method of transferring a facial expression from a subject to a computer generated character that includes receiving a plate with an image of the subject's facial expression, a three-dimensional parameterized deformable model of the subject's face where different facial expressions of the subject can be obtained by varying values of the model parameters, a model of a camera rig used to capture the plate, and a virtual lighting model that estimates lighting conditions when the image on the plate was captured.

Abstract: Some implementations of the disclosure are directed to techniques for facial reconstruction from a sparse set of facial markers. In one implementation, a method comprises: obtaining data comprising a captured facial performance of a subject with a plurality of facial markers; determining a three-dimensional (3D) bundle corresponding to each of the plurality of facial markers of the captured facial performance; using at least the determined 3D bundles to retrieve, from a facial dataset comprising a plurality of facial shapes of the subject, a local geometric shape corresponding to each of the plurality of the facial markers; and merging the retrieved local geometric shapes to create a facial reconstruction of the subject for the captured facial performance.

Abstract: A method of transferring a facial expression from a subject to a computer generated character that includes receiving a plate with an image of the subject's facial expression, a three-dimensional parameterized deformable model of the subject's face where different facial expressions of the subject can be obtained by varying values of the model parameters, a model of a camera rig used to capture the plate, and a virtual lighting model that estimates lighting conditions when the image on the plate was captured.

Abstract: The movement of elements through a region of three dimensional (3D) space is simulated by utilizing a number of two dimensional (2D) grids to define the region of 3D space. Movement information is associated with each grid point of each 2D grid, and changed over a time period. For each element in 3D space, movement information is interpolated from the grid points of a pair of 2D grids that lie on opposite sides of the element. The interpolated movement information is used to advect the elements through the region of 3D space.