Presently disclosed is a method for co-segmenting three-dimensional models represented by sparse and low-rank feature, comprising: pre-segmenting each three-dimensional model of a three-dimensional model class to obtain three-dimensional model patches for the each three-dimensional model; constructing a histogram for the three-dimensional model patches of the each three-dimensional model to obtain a patch feature vector for the each three-dimensional model; performing a sparse and low-rank representation to the patch feature vector for the each three-dimensional model to obtain a representation coefficient and a representation error of the each three-dimensional model; determining a confident representation coefficient for the each three-dimensional model according to the representation coefficient and the representation error of the each three-dimensional model; and clustering the confident representation coefficient of the each three-dimensional model to co-segment the each three-dimensional model respectively.

A shape generation system can generate a three-dimensional (3D) model of an object from a two-dimensional (2D) image of the object by projecting vectors onto light cones created from the 2D image. The projected vectors can be used to more accurately create the 3D model of the object based on image element (e.g., pixel) values of the image.

A shape generation system can generate a three-dimensional (3D) model of an object from a two-dimensional (2D) image of the object by projecting vectors onto light cones created from the 2D image. The projected vectors can be used to more accurately create the 3D model of the object based on image element (e.g., pixel) values of the image.

A method for generating 3D printing points may include obtaining a Steiner patch that is part of a tessellation approximation of the 3D object, determining a parametric curve of a slicing plane and the Steiner patch, determining a classification of the parametric curve, sampling, based upon the classification, first and second points spaced by a parametric spacing along the parametric curve, determining a Euclidean spacing of the first and second points, and comparing the Euclidean spacing to a predefined spacing threshold. In response to the Euclidean spacing failing to satisfy the predefined threshold, sampling a third point along the parametric curve between the first and second points, generating 3D printing points in Euclidean space for the object based upon the first point, second point and third point sampled along the parametric curve.

A method for generating 3D printing points may include obtaining a Steiner patch that is part of a tessellation approximation of the 3D object, determining a parametric curve of a slicing plane and the Steiner patch, determining a classification of the parametric curve, sampling, based upon the classification, first and second points spaced by a parametric spacing along the parametric curve, determining a Euclidean spacing of the first and second points, and comparing the Euclidean spacing to a predefined spacing threshold. In response to the Euclidean spacing failing to satisfy the predefined threshold, sampling a third point along the parametric curve between the first and second points, generating 3D printing points in Euclidean space for the object based upon the first point, second point and third point sampled along the parametric curve.

Systems and methods are provided for collecting measurement data for a three-dimensional object. In embodiments, a computer model of the three-dimensional object is generated that correlates points on the three-dimensional object with points in three-dimensional space; the computer model is used to collect measurement data of the three-dimensional object and associate the collected measurement data with points in three-dimensional space; and a plan view computer model of the three-dimensional object is generated that depicts the measurement data in two dimensions and that associates the depicted measurement data with points in three-dimensional space.

A 3D shape matching method and a 3D shape matching device based on 3D local feature description using SGHs are provided. In the method, the spherical neighborhood of the feature point is not only divided based on space but also divided based on geometry, the spherical neighborhood of the feature point is not only divided based on the radial direction and the azimuth respectively but also divided based on the elevation, and the spherical neighborhood of the feature point is not only divided based on the deviation angle deviating from the z axis but also divided based on the deviation angle deviating from the x axis. When the deviation angle deviating from the z axis of the spherical neighborhood is divided, the deviation angle is divided more densely where it is closer to the positive direction of the z axis.

Devices, systems, and methods of generating and providing a target topographic map for finishing a photomask blank are disclosed. A method includes receiving topographic data corresponding to an uncompleted photomask blank, receiving functional specifications for flatness of an acceptable photomask blank, and generating the target topographic map for first and/or second major surfaces of the blank, which provides instructions for removing material from the first and/or second major surfaces such that the first and second major surfaces achieve a flatness that passes each functional specification. The amount of material removed reflects a reduction in material necessary to pass the functional specifications. The method further includes transmitting the target topographic map to the finishing device to utilize a finishing technique to implement changes to the photomask blank according to the target topographic map by removing the material from the photomask blank to achieve a photomask blank that passes the functional specifications.

Devices, systems, and methods of generating and providing a target topographic map for finishing a photomask blank are disclosed. A method includes receiving topographic data corresponding to an uncompleted photomask blank, receiving functional specifications for flatness of an acceptable photomask blank, and generating the target topographic map for first and/or second major surfaces of the blank, which provides instructions for removing material from the first and/or second major surfaces such that the first and second major surfaces achieve a flatness that passes each functional specification. The amount of material removed reflects a reduction in material necessary to pass the functional specifications. The method further includes transmitting the target topographic map to the finishing device to utilize a finishing technique to implement changes to the photomask blank according to the target topographic map by removing the material from the photomask blank to achieve a photomask blank that passes the functional specifications.

In one embodiment, a method includes receiving sensor data of a scene captured using one or more sensors, generating (1) a number of virtual surfaces representing a number of detected planar surfaces in the scene and (2) a point cloud representing detected features of objects in the scene based on the sensor data, assigning each point in the point cloud to one or more of the number of virtual surfaces, generating occupancy volumes for each of the number of virtual surfaces based on the points assigned to the virtual surface, generating a datastore including the number of virtual surfaces, the occupancy volumes of each of the number of virtual surfaces, and a spatial relationship between the number of virtual surfaces, receiving a query, and sending a response to the query, the response including an identified subset of the plurality of virtual surfaces in the datastore that satisfy the query.