Trimble Ab

Trimble Inc.

Thomas G Chaperon

Guillaume Tremblay

Troy Lane Brown

Jorge Hernandez Londono

Arnaud Boucherat

Fabrice Monnier

Andrés Serna

A method of rendering a three-dimensional point cloud in a two-dimensional display includes inputting the three-dimensional point cloud that includes three-dimensional coordinates of a set of points, creating a depth buffer for the three-dimensional point cloud that includes depth data for the set of points from a viewpoint location. The method further includes determining a foreground depth buffer by, for each respective pixel area of the two-dimensional display, determining a foreground depth by detecting a closest point to the viewpoint location among a subset of the set of points corresponding to the respective pixel area, and assigning a depth of the closest point as the foreground depth for the respective pixel area. The method further includes filtering the depth buffer to obtain a filtered depth buffer by removing points that are not in the foreground, and outputting the filtered depth buffer to the two-dimensional display.

Enhanced three-dimensional point cloud rendering

A method of colorizing a 3D point cloud includes receiving the 3D point cloud, receiving a 2D color image acquired by a camera, creating a 2D intensity image of the 3D point cloud based on intrinsic and extrinsic parameters of the camera, generating a set of refined camera parameters by matching the 2D intensity image and the 2D color image, creating a depth buffer for the 3D point cloud using the set of refined camera parameters, determining a foreground depth for each respective pixel of the depth buffer, and coloring the point cloud by, for each respective point of the 3D point cloud: upon determining that the respective point is in the foreground, assigning a color of a corresponding pixel in the 2D color image to the respective point; and upon determining that the respective point is not in the foreground, not assigning any color to the respective point.

Scan colorization with an uncalibrated camera

A method to integrate all observations, e.g., surveying data in the form of total station data, images, and point clouds) from a surveying instrument that functions as a total station, a camera(s), and a scanner. The method provides an overall adjustment to maximize the accuracy of the adjustment by using all three types of available surveying data, and the method may be labeled an overall adjustment or integrated network adjustment to provide accurate station or instrument position data for a geodatabase for a surveyed site. The overall adjustment method allows all three types of surveying data to influence the results of the adjustment, and this achieved by generating a small number of virtual observations from the image and scan data that are of a form that allows them to be combined with or considered concurrently with the real observations from the total station as part of a single network adjustment.

Integrating point cloud scans, image data, and total station data from a surveying instrument into one adjustment

Methods and apparatus are provided for processing data representing three-dimensional points organized in a data structure wherein each point has multiple components, the data is organized in a respective layer per component, each layer is segmented in cells of a two-dimensional grid, the cells are arranged such that the components of a given point are contained in corresponding cells of multiple layers, the cells are grouped in patches by layer, and the patches are arranged such that the components of an array of points is represented by corresponding patches of multiple layers. At least one first criterion and at least one second criterion are obtained. Data are retrieved from cells of patches meeting the at least one first criterion and from layers meeting the at least one second criterion. The retrieved data are processed to obtain a derivative data set.

Methods and apparatus for point cloud data processing

Methods and devices for processing image data stored as three-dimensional point clouds related to a scene by selecting a profile definable in a two-dimensional surface, and matching the profile to one or more subsets of the cloud of points to identify surfaces in the scene having the same profile so that data sets representing the successive matched surface portions can be generated to provide a surface model of all or part of the scene.

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Paris, France

Thomas G Chaperon