Abstract: A system interactively edits a graphics object. The system includes a user interface for setting editing parameters, and providing a model of the graphics object. An adaptively sample distance field is generated from the model, and an interactive editor manipulates the adaptively sampled distance field. The manipulated adaptively sampled distance field is then converted to rendering primitives to be rendered by a rendering engine.

Abstract: A method traverses a bi-tree stored in a memory to locate application specific data stored in the memory and associated with the bi-tree. The bi-tree comprises a spatial partitioning of an N-dimensional space into a hierarchy of cells. Starting from a root cell enclosing the N-dimensional space, each cell is successively and conditionally partitioned into 2N child cells along the cell's N mid-planes. Each cell of the bi-tree has associated characteristics comprising the application specific data and child cells are indexed directly from a parent cell. First, a set of locational codes, a cell of the bi-tree, and a termination condition are specified. Next, the characteristics of the cell are tested to see if they satisfy the termination condition. If the termination condition is not satisfied, an arithmetic operation on the set of locational codes is performed to directly index a next cell to be tested. Otherwise, the cell identifies a target cell.

Abstract: A method edits a surface of a graphics object with a computer implemented tool by first generating an adaptively sampled distance field from the graphics object, and defining a tool path. A gradient for each point on the surface nearest to each location of the tool on the tool path is determined, as well as the distance between each point and each location. The tool is iteratively moved along the tool path in a direction of the gradient and an amount proportional to the distance to maintain the tool on the surface of the object while editing the surface of the object.

Abstract: A method dynamically generates rendering elements for a graphics model. The model is first converted to an adaptively sampled distance field including surface cells representing a surface of the model. A visibility element is determined for each surface cell. A set of active cells is determined, where each active cell is associated with one of the surface cells of the adaptively sample distance field, and each active cell has a corresponding visibility element. Rendering elements are determined for each active cell. Active cells are added and deleted from the set of active cells dynamically according to a weight determined for each active cell by a weighting function. The weight of each active cell can depend on viewing and shading parameters. Rendering elements are dynamically generated when active cells are added to the set of active cells and dynamically deleted when active cells are deleted from the set of active cells.

Abstract: A method generates a textured range image by first acquiring a first image of a scene illuminated with ambient light, and acquiring a second image of the scene illuminated with direct light. The first and second images are combined to determine the textured range image.

Abstract: A camera generates a textured range image. The camera includes a single lens, and a flash substantially co-located with the lens. The camera acquires a first image of a scene from a point of view with ambient light, and a second image of the scene from the point of view with direct light of the flash. The first image and the seconds image are then combined by a divider to generate the textured range image.

Abstract: A method determines a distance from a 3D point to a 3D surface from a 2D projected range image. A projected distance and a cliff distance from the 3D point to the 3D surface are determined using the projected range image. The projected distance and the cliff distance are then combined to determine the distance from the 3D point to the 3D surface.

Abstract: A method edits a 3D model using 2D images. First, a projected range image is generated from a 3D model. The projected range image is edited using a 2D editor. A projected distance and a cliff distance from a plurality of 3D points to a 3D surface of the 3D model are determined using the edited projected range image. The projected distance and the cliff distance of each of the 3D points are combined to determine a distance from each 3D point to the 3D surface so that the distances forming a distance field of the edited 3D model.

Abstract: A method for modeling a graphics object generates a model of the graphics object. An adaptively sampled distance field is generated from the model according to an error measure. The adaptively sampled distance field includes interior, surface, and exterior cells. Each cell stores distance values, and the distance values of the surface cells always satisfy the error measure. A subset of cells are selected from the adaptively sampled distance field. The subset of cells only include interior and exterior cells. The selected cells are subdivided and the distance values for the subdivided cells are regenerated, until the distance values of the subdivided cells satisfy the error measure.

Abstract: A method edits a graphics object with a computer implemented tool by first representing the graphics object by an adaptively sampled distance field, and defining a mask by a distance field. Then, the tool is iteratively moved with respect to the object while constraining the movement according to the mask to edit the object.

Abstract: A method sculpts an object expressed as a model. A hierarchical distance field is generated from the model according to generation parameters. The hierarchical distance field is edited according to editing parameters, and the hierarchical distance field is rendered while editing. To generate the hierarchical distance field, the object distance field is enclosed with an object bounding box. The enclosed object distance field is partitioned into a plurality of cells. Each cell has a size corresponding to detail of the object distance field and a location with respect to the object bounding box. A set of values of the enclosed object distance field is sampled for each cell. A method for reconstructing the portion of the distance field enclosed by the cell is specified for each cell.

Abstract: The invention provides a method for representing a device color gamut as a detail directed hierarchical distance field. A distance field representing the device color gamut is enclosed with a bounding box. The enclosed distance field is partitioned into a plurality of cells. Each cell has a size corresponding to detail of the continuous distance field and a location with respect to the bounding box. A set of values of the enclosed distance field is sampled for each cell. A method for reconstructing the portion of the distance field enclosed by the cell is specified. The size, the location, the set of values, and the method for reconstructing is stored in a memory to enable reconstruction of the device color gamut by applying the reconstruction methods of the cells to the values.

Abstract: A method generates a detail directed hierarchical representation of orientations of a surface of a graphics model. The surface of the graphics model is partitioned into surface cells, each surface cell enclosing a portion of the surface. The surface cells are stored in a hierarchical data structure having levels, wherein the number of levels for a particular portion of the surface is determined by surface detail of the particular portion. A visibility element of the enclosed portion of the surface is determined for each surface cell, the visibility element specifying an axis and a spread defining a range of normal values of the enclosed portion of the surface. The visibility element is stored with the associated surface cell. The surface detail of the particular portion can be determined by a degree of curvature and shading parameters of the surface of the particular portion.

Abstract: A method is described for modeling interactions between models. A first adaptively sampled distance field having a first spatial hierarchy for a first model is generated, and a second adaptively sampled distance field having a second spatial hierarchy for a second model is generated. During each time step, a potential overlap region is determined using the spatial hierarchies of the first and second adaptively sampled distance fields. When the potential overlap region is non-empty, a third adaptively sampled distance field is generated from the first and second adaptively sampled distance fields using a first interaction procedure and first properties and a fourth adaptively sampled distance field is generated from the first and second adaptively distance fields using a second interaction procedure and second properties to model the interactions between the first and second models.

Abstract: A method dynamically generates rendering elements for a graphics model. The model is first converted to an adaptively sampled distance field including surface cells representing a surface of the model. A visibility element is determined for each surface cell. A set of active cells is determined, where each active cell is associated with one of the surface cells of the adaptively sample distance field, and each active cell has a corresponding visibility element. Rendering elements are determined for each active cell. Active cells are added and deleted from the set of active cells dynamically according to a weight determined for each active cell by a weighting function. The weight of each active cell can depend on viewing and shading parameters. Rendering elements are dynamically generated when active cells are added to the set of active cells and dynamically deleted when active cells are deleted from the set of active cells.

Abstract: A method is described for determining a 2D gradient magnitude image from a range image of an object. The range image includes intensity values at pixel locations. The intensity values correspond to distances to a surface of the object. For each pixel (i,j) in the range image, a horizontal central difference dx value and a vertical central difference dy value are determined. Then, the 2D gradient magnitude image value at each pixel (i,j) is set to 0.5*sqrt(dx2+dy2+4). The range image can be scaled so that a unit intensity value at each pixel corresponds to a unit distance value. The magnitude of a gradient at a 3D point p can then be determined from the scaled range image and the gradient magnitude image. First, a perpendicular projection (x,y) of p onto the scaled range image is computed. Next, a gradient magnitude at (x,y) is interpolated from the corresponding values of the 2D gradient magnitude image near the location (x,y).

Abstract: A method edits a graphics object by first representing the graphics object by an adaptively sampled distance field. A portion of the adaptively sampled distance field is selected for editing and converted to a triangle model. The triangle model is then deformed, the adaptively sampled distance field is regenerated from the deformed triangle model.

Abstract: A method models a plurality of graphics models by generating a first adaptively sampled distance field for a first model, and generating a second adaptively sampled distance field for a second model. Locations in the first adaptively are sampled distance field to determine a distance value for each location. The second adaptively sampled distance field is sampled at each location to determine a corresponding feature of the second adaptively sampled distance field. Then, each distance value is modified according to the corresponding feature to determine a second distance value for each location.

Abstract: A method for modeling a graphics object generates a model of the graphics object. An adaptively sampled distance field is generated from the model according to an error measure. The adaptively sampled distance field includes interior, surface, and exterior cells. Each cell stores distance values, and the distance values of the surface cells always satisfy the error measure. A subset of cells are selected from the adaptively sampled distance field. The subset of cells only include interior and exterior cells. The selected cells are subdivided and the distance values for the subdivided cells are regenerated, until the distance values of the subdivided cells satisfy the error measure.

Abstract: A method generates an adaptively sampled distance field of an object by first defining a candidate cell of the adaptively sampled distance field. Then, distance values for the candidate cell are determined and stored in a bounded distance tree. The candidate cell is recursively subdividing into subdivided cells of the adaptively sampled distance field while determining and storing corresponding distance values of the subdivided cells in the bounded distance tree until a termination condition is reached. Lastly, the distance values are appended to the corresponding cells to generate the adaptively sampled distance field of the object.