Abstract: A method for a computer system includes determining a plurality of positions of portions of a hand of a user simultaneously placed upon a user interface device of the computer system, retrieving a set of display icons in response to the plurality of positions of the portions of the user hand, displaying the display icons from the set of display icons on a display relative to the plurality of positions of the portions of the user hand; while displaying the display icons on the display, determining a user selection of a display icon from the display icons, and performing a function in response to the user selection of the display icon.

Abstract: A method for a computer system includes determining a plurality of positions of portions of a hand of a user simultaneously placed upon a user interface device of the computer system, retrieving a set of display icons in response to the plurality of positions of the portions of the user hand, displaying the display icons from the set of display icons on a display relative to the plurality of positions of the portions of the user hand; while displaying the display icons on the display, determining a user selection of a display icon from the display icons, and performing a function in response to the user selection of the display icon.

Abstract: Mesh data and other proximity information from the mesh of one model can be transferred to the mesh of another model, even with different topology and geometry. A correspondence can be created for transferring or sharing information between points of a source mesh and points of a destination mesh. Information can be “pushed through” the correspondence to share or otherwise transfer data from one mesh to its designated location at another mesh. Correspondences can be created based on parameterization information, such as UV sets, one or more maps, harmonic parameterization, or the like. A collection of “feature curves” may be inferred or user-placed to partition the source and destination meshes into a collection of “feature regions” resulting in partitions or “feature curve networks” for constructing correspondences between all points of one mesh and all points of another mesh.

Abstract: A method for determining interior coordinates is disclosed. The method includes receiving information specifying an object having a plurality of sites and a boundary. Interior coordinates associated with each of the plurality of sites are determined based on the boundary. The interior coordinate associated with each of the plurality of sites represent a system of coordinates that satisfy several properties, including non-negativity and interior locality. At least one value associated with the plurality of sites is then interpolated using the interior coordinates.

Abstract: Mesh data and other proximity information from the mesh of one model can be transferred to the mesh of another model, even with different topology and geometry. A correspondence can be created for transferring or sharing information between points of a source mesh and points of a destination mesh. Information can be “pushed through” the correspondence to share or otherwise transfer data from one mesh to its designated location at another mesh. Correspondences can be authored on a source mesh by drawing or placing one or more geometric primitives (e.g., points, lines, curves, volumes, etc.) at the source mesh and corresponding geometric primitives at the destination mesh. A collection of “feature curves” may be placed to partition the source and destination meshes into a collection of “feature regions” resulting in partitions or “feature curve networks” for constructing correspondences between all points of one mesh and all points of another mesh.

Abstract: Systems and methods are disclosed allowing data and other information from one model to be transferred to another model. A surface correspondence between meshes of the models can be created that provides a transfer or sharing of information to include all points of one mesh and all points of the other mesh. Additionally, a volume correspondence between the models can be created to transfer information found within corresponding volumes or other n-D spaces associated with the models. Mesh information and other data at, near, or otherwise within a volume or other n-D space associated with one model can be “pushed through” the volume correspondences to transfer the data to its designated location on, at, near, or otherwise within a corresponding volume or other n-D space associated with the other model.

Abstract: A method for determining interior coordinates is disclosed. The method includes receiving information specifying an object having a plurality of sites and a boundary. Interior coordinates associated with each of the plurality of sites are determined based on the boundary. The interior coordinate associated with each of the plurality of sites represent a system of coordinates that satisfy several properties, including non-negativity and interior locality. At least one value associated with the plurality of sites is then interpolated using the interior coordinates.

Abstract: A method for determining interior coordinates is disclosed. The method includes receiving information specifying an object having a plurality of sites and a boundary. Interior coordinates associated with each of the plurality of sites are determined based on the boundary. The interior coordinate associated with each of the plurality of sites represent a system of coordinates that satisfy several properties, including non-negativity and interior locality. At least one value associated with the plurality of sites is then interpolated using the interior coordinates.

Abstract: Function spaces defined by scaling functions are used to generate bandlimited noise octaves and other attribute data sets. Scaling functions are basis functions that admit multiresolution analysis and include piecewise constant scaling functions, piecewise polynomial scaling functions, bandlimited scaling functions, Daubeschies scaling functions, as well as other multiresolution analysis scaling basis functions known to those of skill in the art. Scaling basis functions can be locally supported or have infinite support. The properties of the scaling basis functions used to construct bandlimited noise octaves may ensure that any bandlimited noise octave at resolution level N is orthogonal to bandlimited noise octaves and their associated scaling basis functions at all resolution levels less than N. Bandlimited noise octaves can be scaled to any resolution level and guaranteed to have no effect on images at any lower resolution level.

Abstract: Function spaces defined by scaling functions are used to generate bandlimited noise octaves and other attribute data sets. Scaling functions are basis functions that admit multiresolution analysis and include piecewise constant scaling functions, piecewise polynomial scaling functions, bandlimited scaling functions, Daubeschies scaling functions, as well as other multiresolution analysis scaling basis functions known to those of skill in the art. Scaling basis functions can be locally supported or have infinite support. The properties of the scaling basis functions used to construct bandlimited noise octaves may ensure that any bandlimited noise octave at resolution level N is orthogonal to bandlimited noise octaves and their associated scaling basis functions at all resolution levels less than N. Bandlimited noise octaves can be scaled to any resolution level and guaranteed to have no effect on images at any lower resolution level.

Abstract: Slices of N dimensions can be extracted from bandlimited data sets of M dimensions. N is any arbitrary value less than N. A value of a slice is defined by an evaluation of an integral of the bandlimited data set weighted by a filter scaling function orientated along the normal of the slice. Due to the properties of the bandlimited data set, the slice is bandlimited in N dimensions as well. The filter scaling function diminishes at substantially the same rate as the aliasing frequency of the bandlimited data set in the normal direction. The convolution of a scaling basis function used to construct the bandlimited data with itself defines the filter scaling function. A scaling basis function widened in the direction of the normal can approximate the filter scaling function in some cases. Quadrature can approximate the value of the integral. Slices may or may not be axis aligned.

Abstract: Mesh data and other proximity information from the mesh of one model can be transferred to the mesh of another model, even with different topology and geometry. A correspondence can be created for transferring or sharing information between points of a source mesh and points of a destination mesh. Information can be “pushed through” the correspondence to share or otherwise transfer data from one mesh to its designated location at another mesh. Correspondences can be created based on parameterization information, such as UV sets, one or more maps, harmonic parameterization, or the like. A collection of “feature curves” may be inferred or user-placed to partition the source and destination meshes into a collection of “feature regions” resulting in partitions or “feature curve networks” for constructing correspondences between all points of one mesh and all points of another mesh.

Abstract: Systems and methods are disclosed allowing data and other information from one model to be transferred to another model. A surface correspondence between meshes of the models can be created that provides a transfer or sharing of information to include all points of one mesh and all points of the other mesh. Additionally, a volume correspondence between the models can be created to transfer information found within corresponding volumes or other n-D spaces associated with the models. Mesh information and other data at, near, or otherwise within a volume or other n-D space associated with one model can be “pushed through” the volume correspondences to transfer the data to its designated location on, at, near, or otherwise within a corresponding volume or other n-D space associated with the other model.

Abstract: Data tiles can be combined to form attribute data sets for use in generating computer graphics images. Tiles may be arranged in a regular grid pattern or in arbitrary, irregular positions. Tiles can be overlapped slightly and blended to hide tile boundaries. The value of the combined data set in an overlap region may be a weighted sum of values from the tiles. To compensate for reduced variance and contrast caused by blending, the values in overlap regions can be scaled by a variance correction factor. The variance correction factor is the inverse of the reduction in variance from the source tiles. Tile values can be scaled by their weights and variance correction values at the time they are combined or in advance, if the pattern of tile overlaps are consistent. Data tiles can be comprised of bandlimited noise data or other data types.

Abstract: Function spaces defined by scaling functions are used to generate bandlimited noise octaves and other attribute data sets. Scaling functions are basis functions that admit multiresolution analysis and include piecewise constant scaling functions, piecewise polynomial scaling functions, bandlimited scaling functions, Daubeschies scaling functions, as well as other multiresolution analysis scaling basis functions known to those of skill in the art. Scaling basis functions can be locally supported or have infinite support. The properties of the scaling basis functions used to construct bandlimited noise octaves may ensure that any bandlimited noise octave at resolution level N is orthogonal to bandlimited noise octaves and their associated scaling basis functions at all resolution levels less than N. Bandlimited noise octaves can be scaled to any resolution level and guaranteed to have no effect on images at any lower resolution level.

Abstract: Mesh data and other proximity information from the mesh of one model can be transferred to the mesh of another model, even with different topology and geometry. A correspondence can be created for transferring or sharing information between points of a source mesh and points of a destination mesh. Information can be “pushed through” the correspondence to share or otherwise transfer data from one mesh to its designated location at another mesh. Correspondences can be authored on a source mesh by drawing or placing one or more geometric primitives (e.g., points, lines, curves, volumes, etc.) at the source mesh and corresponding geometric primitives at the destination mesh. A collection of “feature curves” may be placed to partition the source and destination meshes into a collection of “feature regions” resulting in partitions or “feature curve networks” for constructing correspondences between all points of one mesh and all points of another mesh.

Abstract: Techniques are disclose that may assist animators or other artists working with models. Information from a plurality of meshes in a collection may be blended or combined using correspondences between pairs of the meshes. Meshes in the collection may include different topologies and geometries. The combined information can be used to create combinations of data that reflect new topologies, geometries, scalar fields, hair styles, or the like that may be transferred to a mesh of new or existing models.

Abstract: Data tiles can be combined to form attribute data sets for use in generating computer graphics images. Tiles may be arranged in a regular grid pattern or in arbitrary, irregular positions. Tiles can be overlapped slightly and blended to hide tile boundaries. The value of the combined data set in an overlap region may be a weighted sum of values from the tiles. To compensate for reduced variance and contrast caused by blending, the values in overlap regions can be scaled by a variance correction factor. The variance correction factor is the inverse of the reduction in variance from the source tiles. Tile values can be scaled by their weights and variance correction values at the time they are combined or in advance, if the pattern of tile overlaps are consistent. Data tiles can be comprised of bandlimited noise data or other data types.

Abstract: Slices of N dimensions can be extracted from bandlimited data sets of M dimensions. N is any arbitrary value less than N. A value of a slice is defined by an evaluation of an integral of the bandlimited data set weighted by a filter scaling function orientated along the normal of the slice. Due to the properties of the bandlimited data set, the slice is bandlimited in N dimensions as well. The filter scaling function diminishes at substantially the same rate as the aliasing frequency of the bandlimited data set in the normal direction. The convolution of a scaling basis function used to construct the bandlimited data with itself defines the filter scaling function. A scaling basis function widened in the direction of the normal can approximate the filter scaling function in some cases. Quadrature can approximate the value of the integral. Slices may or may not be axis aligned.

Abstract: Function spaces defined by scaling functions are used to generate bandlimited noise octaves and other attribute data sets. Scaling functions are basis functions that admit multiresolution analysis and include piecewise constant scaling functions, piecewise polynomial scaling functions, bandlimited scaling functions, Daubeschies scaling functions, as well as other multiresolution analysis scaling basis functions known to those of skill in the art. Scaling basis functions can be locally supported or have infinite support. The properties of the scaling basis functions used to construct bandlimited noise octaves may ensure that any bandlimited noise octave at resolution level N is orthogonal to bandlimited noise octaves and their associated scaling basis functions at all resolution levels less than N. Bandlimited noise octaves can be scaled to any resolution level and guaranteed to have no effect on images at any lower resolution level.