Abstract: A system includes one or more processors that are configured to compensate a measurement tool by performing a method. The method includes capturing a first data using the measurement tool. The method further includes capturing a second data using the measurement tool. The method further includes detecting a first natural feature in the first data. The method further includes computing a difference in positions of the first natural feature in the first data and the second data respectively. The method further includes computing a compensation parameter to adjust the measurement tool based on the difference computed.

Abstract: A system includes a three-dimensional (3D) scanner that captures a 3D point cloud corresponding to one or more objects in a surrounding environment. The system further includes a camera that captures a control image by capturing a plurality of images of the surrounding environment, and an auxiliary camera configured to capture an ultrawide-angle image of the surrounding environment. One or more processors of the system colorize the 3D point cloud using the ultrawide-angle image by mapping the ultrawide-angle image to the 3D point cloud. The system performs a limited system calibration before colorizing each 3D point cloud, and a periodic full system calibration before/after a plurality of 3D point clouds are colorized.

Abstract: A system includes a three-dimensional (3D) scanner that captures a 3D point cloud corresponding to one or more objects in a surrounding environment. The system further includes a camera that captures a control image by capturing a plurality of images of the surrounding environment, and an auxiliary camera configured to capture an ultrawide-angle image of the surrounding environment. One or more processors of the system colorize the 3D point cloud using the ultrawide-angle image by mapping the ultrawide-angle image to the 3D point cloud. The system performs a limited system calibration before colorizing each 3D point cloud, and a periodic full system calibration before/after a plurality of 3D point clouds are colorized.

Abstract: A system includes a three-dimensional (3D) scanner, a camera with a viewpoint that is different from a viewpoint of the 3D scanner, and one or more processors coupled with the 3D scanner and the camera. The processors access a point cloud from the 3D scanner and one or more images from the camera, the point cloud comprises a plurality of 3D scan-points, a 3D scan-point represents a distance of a point in a surrounding environment from the 3D scanner, and an image comprises a plurality of pixels, a pixel represents a color of a point in the surrounding environment. The processors generate, using the point cloud and the one or more images, an artificial image that represents a portion of the surrounding environment viewed from an arbitrary position in an arbitrary direction, wherein generating the artificial image comprises colorizing each pixel in the artificial image.

Abstract: A system includes a first type of measurement device that captures first 2D images, a second type of measurement device that captures 3D scans. A 3D scan includes a point cloud and a second 2D image. The system also includes processors that register the first 2D images. The method includes accessing the 3D scan that records at least a portion of the surrounding environment that is also captured by a first 2D image. Further, 2D features in the second 2D image are detected, and 3D coordinates from the point cloud are associated to the 2D features. 2D features are also detected in the first 2D image, and matching 2D features from the first 2D image and the second 2D image are identified. A position and orientation of the first 2D image is calculated in a coordinate system of the 3D scan using the matching 2D features.

Abstract: Examples described herein provide a method that includes capturing data about an environment. The method further includes generating a database of two-dimensional (2D) features and associated three-dimensional (3D) coordinates based at least in part on the data about the environment. The method further includes determining a position (x, y, z) and an orientation (pitch, roll, yaw) of a device within the environment based at least in part on the database of 2D features and associated 3D coordinates. The method further includes causing the device to display, on a display of the device, an augmented reality element at a predetermined location based at least in part on the position and the orientation of the device.

Abstract: A system includes a three-dimensional (3D) scanner that captures a 3D point cloud corresponding to one or more objects in a surrounding environment. The system further includes a camera that captures a control image by capturing a plurality of images of the surrounding environment, and an auxiliary camera configured to capture an ultrawide-angle image of the surrounding environment. One or more processors of the system colorize the 3D point cloud using the ultrawide-angle image by mapping the ultrawide-angle image to the 3D point cloud. The system performs a limited system calibration before colorizing each 3D point cloud, and a periodic full system calibration before/after a plurality of 3D point clouds are colorized.

Abstract: A point cloud is colorized by mapping a color image using an intensity image. The mapping includes detecting multiple features from the intensity image using a feature-extraction algorithm. A feature is extracted that is not within a predetermined vicinity of an edge in the intensity image. A template is created by selecting a portion of a predetermined size from the intensity image with the feature at the center. A search window is created with the same size as the template by selecting a portion of a luminance image as a search space. The luminance image is obtained from the color image. A cost value is computed for each pixel of the search space by comparing image gradients of the template and the search window. A matching point is determined in the color image corresponding to the feature based on the cost value for each pixel of search space.

Abstract: A system includes a three-dimensional (3D) scanner that captures a 3D point cloud with multiple scan-points corresponding to one or more objects scanned in a surrounding environment. The system further includes a camera that captures an image of the surrounding environment. The system further includes one or more processors that colorize the scan-points in the 3D point cloud using the image. Colorizing a scan-point includes determining, for the scan-point, a corresponding pixel in the image by back-projecting the scan-point to the camera. Colorizing the scan-point includes assigning, to the scan-point, a color-value based on the corresponding pixel. Colorizing the scan-point includes computing, for the scan-point, a distance of the scan-point from the camera. Colorizing the scan-point includes determining, based on the distance, that the scan-point is occluded from only one of the camera and the 3D scanner, and in response, updating the color-value assigned to the scan-point.

Abstract: A computer-implemented method is performed by one or more processors to automatically register a plurality of captured data obtained using a respective measurement device, each of the captured data is obtained separately. The computer-implemented method includes accessing a first captured data of a portion of an environment, and a first image corresponding to said portion of the environment captured from a known relative position and angle with respect to the first captured data. Further, from the plurality of captured data, a second captured data is identified that has at least a partial overlap with said portion, the second captured data is identified based on a corresponding second image. The second image is captured from a known relative position and angle with respect to the second captured data. The method further includes transforming the second captured data and/or the first captured data to a coordinate system.

Abstract: A method includes mapping attribute information from a sensor with 3D coordinates from a 3D measurement device, wherein the mapping comprises blending the attribute information to avoid boundary transition effects. The blending includes representing the 3D coordinates that are captured using a plurality of voxel grids. The blending further includes converting the plurality of voxel grids to a corresponding plurality of multi-band pyramids, wherein each multi-band pyramid comprises a plurality of levels, each level storing attribute information for a different frequency band. The blending further includes computing a blended multi-band pyramid based on the plurality of voxel grids by combining corresponding levels from each of the multi-band pyramids. The blending further includes converting the blended multi-band pyramid into a blended voxel grid. The blending further includes outputting the blended voxel grid.

Abstract: A 3D measurement system, a laser scanner and a measurement device are provided. The system includes a 3D measurement device and a 360 degree image acquisition system coupled in a fixed relationship to the 3D measurement device. The 360 degree image acquisition system includes a first photosensitive array operably coupled to a first lens, the first lens having a first optical axis in a first direction, the first lens being configured to provide a first field of view greater than 180 degrees. The image acquisition system further includes a second photosensitive array operably coupled to a second lens, the second lens having a second optical axis in a second direction, the second direction is opposite the first direction, the second lens being configured to provide a second field of view greater than 180 degrees. Wherein the first field of view at least partially overlaps with the second field of view.

Abstract: A method includes capturing, by a three-dimensional (3D) scanner, a 3D point cloud, and capturing, by a camera, a control image by capturing and stitching multiple images of the surrounding environment. The method further includes capturing, by an auxiliary camera, an ultrawide-angle calibration image. The method further includes dynamically calibrating the auxiliary camera using the 3D point cloud, the control image, and the calibration image. The calibrating includes extracting a first plurality of features from the control image and extracting a second plurality of features from the calibration image. Further, a set of matching features are determined from the first and second sets of features. A set of control points is generated using the set of matching features by determining points in the 3D point cloud that correspond to the set of matching features. Further, a self-calibration of the auxiliary camera is performed using the set of control points.

Abstract: A three-dimensional (3D) measuring system that includes an external projector and an imager device. The imager device having a projector, a first camera and a second camera. The system further having one or more processors operably coupled to the display, the projector, the first camera and the second camera. The processors are responsive to executable computer instructions when executed on the one or more processors for projecting one or more random patterns on an object, recording one or more stereo images of the object, estimating a position and orientation of an imager device and registering scan data generated from the estimated position and orientation of the imager device into a coordinate system.