Faro Technologies, Inc.

Daniel Pompe

Daniel Flohr

Helmut Kramer

Sebastian Bartmann

Michael Schanz

Martin Ossig

Oliver Zweigle

Reinhard Becker

Louis Bergmann

Manuel Caputo

José Gerardo Gómez Méndez

Zia Ul Azam

Julian Becker

Sebastian Grottel

Raza Ul Azam

Techniques are described to generate a 3D scene by mapping a point cloud with a 2D image, and colorize portions of the 3D scene synthetically. An input is received to select, from the 3D scene, a portion to be colorized synthetically. The colorizing includes generating a reflectance image based on an intensity image of the point cloud. The colorizing further includes generating an occlusion mask that identifies the selected portion in the reflectance image. The colorizing further includes estimating, using a trained machine learning model, a color for each of the one or more points in the selected portion based on the reflectance image, the occlusion mask, and the 2D image. The 3D scene is updated by using the estimated colors from the trained machine learning model to colorize the selected portion.

Scan color restoration

A scanner that can detect types of targets in a scan are includes a processor, housing and a 3D scanner disposed within the housing The processor is configured to identify locations of one more checkerboard targets disposed in the scan area by: identifying transition locations where adjacent segments on a single scan line transition from a first color to a second color; recording locations of the transition locations as first to second color transition locations; identifying and recording transition locations where adjacent segments on a single scan line transition from the second color to the first color as second to first color transition locations; forming a transition line through adjacent first to second color transition locations and adjacent second to first color transition locations; and identifying a location of a checkerboard target based on the transition line.

Laser scanner with target detection

A scanner that can detect types of targets in a scan are includes a processor, housing and a 3D scanner disposed within the housing. The 3D scanner has a light source, a beam steering unit, a first angle measuring device, a second angle measuring device, and a light receiver, the beam steering unit cooperating with the light source and light receiver to define a scan area, the light source and the light receiver configured to cooperate with the processor system to determine locations a plurality of points in the scan area. In cases where the targets are spheres, the processor is configured to: identify potential sphere center points in the scan area by processing points identified in a single scan line; record locations of potential sphere center points; and compare some or all of the recorded locations to one another to select a sphere center point.

A system of generating a three-dimensional (3D) scan of an environment includes multiple 3D scanners including a first 3D scanner at respective first and second positions. The system further includes a controller coupled to the 3D scanners via a common communications network. The first scanner and second scanner transmit a subset of data to the controller while acquiring a set of 3D coordinates. The controller registers the subsets of data to each other while the sets of 3D coordinates is being acquired.

System and method of registering point cloud data using subsample data

According to one embodiment, a three-dimensional (3D) measuring device is provided. The 3D measuring device includes a processor system that is configured to generate a point cloud representing multiple surfaces. The point cloud includes multiple scan points. Generating the point cloud includes receiving spherical coordinates for a scan point, the spherical coordinates comprising a distance (r), a polar angle (&#x3b8;), and an azimuth angle (&#x3c6;). Generating the point cloud further includes homogenizing a scan point density of the surfaces by filtering the scan points. The homogenizing includes computing a value (p) for the scan point based on the spherical coordinates. Based on the value exceeding a predetermined threshold, storing the scan point as part of the point cloud, and based on the value not exceeding the predetermined threshold, discarding the scan point.

Real-time scan point homogenization for terrestrial laser scanner

A system of generating a three-dimensional (3D) scan of an environment includes multiple 3D scanners including a first 3D scanner at respective first and second positions. The system further includes a controller coupled to the 3D scanners. The first 3D scanner acquires a first set of 3D coordinates, the first set of 3D coordinates having a first portion. The second 3D scanner acquires a second set of 3D coordinates, the second set of 3D coordinates having a second portion. The first portion and the second portion are simultaneously transmitted to the controller by the first 3D scanner and the second 3D scanner respectively, while the first set of 3D coordinates and the second set of 3D coordinates are being acquired. The controller registers the first portion and the second portion to each other while the first set of 3D coordinates and the second set of 3D coordinates are being acquired.

System and method of scanning an environment using multiple scanners concurrently

A method for optically scanning and measuring a scene by a laser scanner includes generating multiple scans; tracking scanner positions with a position-tracking device for the multiple scans and providing tracked scanner positions in response; registering sequentially scans selected from the multiple scans into clusters using registration points or targets and confirming registration of the scans into the clusters according to specified quality criteria being fulfilled; selecting scans from the clusters and forming pairs of scans; forming an intersection of the selected pairs and comparing a size of the intersection with a threshold value obtained based at least in part on the tracked scanner positions; and attempting to register the pairs of scans if the size of the intersection exceeds the threshold value and accepting the registered pairs of scans if the registration is successful.

Registering of a scene disintegrating into clusters with position tracking

A method for automatically generating a three-dimensional (3D) video of a scene by measuring and registering 3D coordinates at a first position and a second position of a 3D measuring device, the 3D video generated by combining two-dimensional images extracted at trajectory points along a trajectory path.

Automated generation of a three-dimensional scanner video

A method for optically scanning and measuring a scene by a three-dimensional (3D) measurement device in which multiple scans are generated to then be registered in a joint coordinate system of the scene. At first at least one cluster is generated from at least one scan, further scans are registered for test purposes in the coordinate system of the cluster, and registering is then confirmed if specified quality criteria are fulfilled and the generated clusters are then joined, for which purpose pairs are formed of selected scans and/or clusters to form pairs, the pairs are registered for test purposes and registering is confirmed if appropriate.

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Stuttgart, Germany

Daniel Pompe