Leica Geosystems Ag

Leica Geosystems Hds, Inc.

Cyra Technologies, Inc.

Jonathan Apollo Kung

Mark Damon Wheeler

Richard William Bukowski

Jerry Samuel Dimsdale

Ben K Kacyra

Laura Michele Downs

Jeffrey Minoru Adachi

Christopher Robin Thewalt

Mark Brunkhart

Dimitrios Ioannou

Laslo Vespremi

Daniel Chudak

Vadim Matov

A computer model of a physical structure (or object) can be generated using context-based hypothesis testing. For a set of point data, a user selects a context specifying a geometric category corresponding to the structure shape. The user specifies at least one seed point from the set that lies on a surface of the structure of interest. Using the context and point data, the system loads points in a region near the seed point(s), and determines the dimensions and orientation of an initial surface component in the context that corresponds to those points. If the selected component is supported by the points, that component can be added to a computer model of the surface. The system can repeatedly find points near a possible extension of the surface model, using the context and current surface component(s) to generate hypotheses for extending the surface model to these points. Well-supported components can be added to the surface model until the surface of the structure of interest has been modeled as far as is well-supported by the point data.

Identification of 3D surface points using context-based hypothesis testing

A representation of a physical object can be displayed even where the amount of geometric data is too large to be stored in resident memory. A primary viewing window displays point data for the object using a substantially even sampling of data at an appropriate point density for the system. At least one auxiliary viewing window displays a two-dimensional representation of the point data. A user can select a portion of the data in the auxiliary window(s), such as by selecting cells of an overlaid grid, to be displayed in the primary window using a rendering such as a 'visible' rendering. The remainder of the displayed data can be displayed using a rendering such as a 'hidden' or &#x201c;transparent&#x201d; rendering. The resolution of the selected region can be increased while maintaining a substantially even spacing among points for the region. The resolution of the unselected region can be decreased accordingly.

Browsers for large geometric data visualization

An improved interface and algorithm(s) can be used to simplify and improve the process for locating an edge from a series of points in a point cloud. An interface can allow the user to select a hint point thought to be near an edge of interest, which can be used to generate an initial edge profile. An interface can allow the user to adjust the fit of the initial profile in cross-section, then can use that profile to generate a profile of the entire edge. A moving fit window can use a moving average to extend the edge and determine proper end locations. An interface then can display the results of the fit to the user and allow the user to adjust the fit, such as by adjusting the end points of the calculated edge. Such a process can be used to fit linear or curvilinear edges, and can fit a number of irregular shapes as well as regular shaped such as 'v-shaped' edges.

Identification of edge regions from 3D point data

An improved interface and algorithm(s) can be used to simplify and improve the process for locating an occluded edge from a series of points in a point cloud. An interface can allow the user to select a hint point thought to be near an edge of interest, which can be used to generate an initial edge profile. An interface can allow the user to adjust the fit of the initial profile in cross-section, then can use that profile to generate a profile of the entire edge. A moving fit window can use an imaginary plane to provide an additional constraint, and can utilize a moving average to extend the edge and determine proper end locations. An interface then can display the results of the fit to the user and allow the user to adjust the fit, such as by adjusting the end points of the calculated edge. Such a process can be used to fit linear or curvilinear occluded edges, and can fit a number of irregular shapes as well as regular shaped edges such as 'v-shaped' edges.

Identification of occluded edge regions from 3D point data

A method relating to a point cloud includes defining a line of sight of a point cloud on a display of a computer, estimating a normal vector for at least one point of the plurality of points, and determining the appearance on the display of at least one point of the plurality of points based on the step of estimating a normal vector. One can use the computer to manipulate the point cloud to display a selected view of the scene and calculate the angle between the normal vector of the at least one point and a line of sight. The step of determining the appearance can include determining the transparency, color or size of the point on the display according to the angle between the normal vector and the line of sight.

Determining appearance of points in point cloud based on normal vectors of points

Large data sets can be stored and processed in real time by combining and registering the large data sets into a single data set. The data can be stored in a data tree structure formed of layers of spatially organized blocks of data. Such storage allows portions of the data to be viewed efficiently, displaying actual point data at an acceptable resolution for the viewing mechanism. Density limited queries can be executed that allow sub-sampling to be done directly and evenly without geometric constraint, to provide a subset of points that is limited in size and includes a spatially-even decomposition of that set of points. This allows the system as a whole to support arbitrarily large point sets while allowing full partitioning functionality, which is efficient to use in both time and space.

System and method for efficient storage and manipulation of extremely large amounts of scan data

An integrated system generates a model of a three-dimensional object. A scanning laser device scans the three-dimensional object and generates a point cloud. The points of the point cloud each indicate a location of a corresponding point on a surface of the object. A first model is generated, responsive to the point cloud, that generates a first model representing constituent geometric shapes of the object. A data file is generated, responsive to the first model, that can be inputted to a computer-aided design system.

Integrated system for quickly and accurately imaging and modeling three-dimensional objects

An apparatus and method are described for acquiring tie-point target locations on a structure that eliminates the need for the user to manually identify features that can be used to register multiple scenes so that they share a single coordinate system. In the present invention, readily identifiable objects, known as targets, are placed on or near the structure. When the structure is scanned, the targets are identified and can then be used in other operations, such as registration.

System and method for acquiring tie-point location information on a structure

An apparatus and method are described for forming 2D views of a structure from 3D point data. In the present invention, a plane is specified and triangulated meshes are intersected with the plane to form a group of polylines. The significant features of each polyline are then extracted, and the features are then connected to form intersection polylines that closely approximate the intersection polylines that would be generated by intersecting the real 3D structure with the specified plane. The final 2D view consists of the connected features extracted from the polylines.

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Oakland, CA, United States of America

Jonathan Apollo Kung