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 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 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 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 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.