Abstract: Surveying apparatus comprising an event-based camera comprising a dynamic vision sensor.

Abstract: A method for automatically establishing an optimal laser scanning plan, the scanning plan indicating an optimal arrangement of multiple distributed standpoints, the arrangement enabling a scanning of an extended object by multiple terrestrial scans of different parts of the object at respective standpoints.

Abstract: A method for surveying an environment by a movable surveying instrument with a progressional capturing of 2D-images by at least one camera and applying a visual simultaneous location and mapping algorithm (VSLAM) or a visual inertial simultaneous location and mapping algorithm (VISLAM) with a progressional deriving of a sparse evolving point cloud of at least part of the environment, and a progressional deriving of a trajectory of movement. The method comprises a progressional matching of the sparse evolving point cloud with a previously derived 3D-geometry, with a minimizing of a function configured to model a distance between the sparse point cloud and the previously derived 3D-geometry and deriving a spatial localization and orientation of the surveying instrument. At least one surveying measurement value of the environment by a spatial measurement unit is combined with the sparse point cloud or the previously derived 3D-geometry.

Abstract: A method for surveying an environment by a movable surveying instrument configured to be carried by a human with a progressional capturing of 2D-images by at least one camera and applying a visual simultaneous location and mapping algorithm (VSLAM) or a visual inertial simultaneous location and mapping algorithm (VISLAM) with a progressional deriving of a sparse evolving point cloud of at least part of the environment, and a progressional deriving of a trajectory of movement. The method comprises a progressional matching of the sparse evolving point cloud with a known CAD-geometry, with a minimizing of a function configured to model a distance between the sparse point cloud and the known CAD-geometry and deriving a spatial localization and orientation of the surveying instrument. At least one surveying measurement value of the environment by a spatial measurement unit is combined with the sparse point cloud or the plan information.

Abstract: Three-dimensional (3D) point cloud generation using a stationary laser scanner and a mobile scanner. The method includes scanning a first part of a surrounding with the stationary laser scanner, obtaining a first 3D point cloud, scanning a second part of the surrounding with the mobile scanner, obtaining a second 3D point cloud, whereby there is an overlap region of the first part and the second part, and aligning the second 3D point cloud to the first 3D point cloud to form a combined 3D point cloud. The positional accuracy of points of the second 3D point cloud is increased by automatically referencing second scanner data of the overlap region, generated by the mobile scanner, to first scanner data of the overlap region, generated by the stationary laser scanner. Therewith, deformations of the second 3D point cloud and its alignment with the first 3D point cloud are corrected.

Abstract: Three-dimensional (3D) point cloud generation using a stationary laser scanner and a mobile scanner. The method includes scanning a first part of a surrounding with the stationary laser scanner, obtaining a first 3D point cloud, scanning a second part of the surrounding with the mobile scanner, obtaining a second 3D point cloud, whereby there is an overlap region of the first part and the second part, and aligning the second 3D point cloud to the first 3D point cloud to form a combined 3D point cloud. The positional accuracy of points of the second 3D point cloud is increased by automatically referencing second scanner data of the overlap region, generated by the mobile scanner, to first scanner data of the overlap region, generated by the stationary laser scanner. Therewith, deformations of the second 3D point cloud and its alignment with the first 3D point cloud are corrected.

Abstract: A method for surveying an environment by a movable surveying instrument configured to be carried by a human with a progressional capturing of 2D-images by at least one camera and applying a visual simultaneous location and mapping algorithm (VSLAM) or a visual inertial simultaneous location and mapping algorithm (VISLAM) with a progressional deriving of a sparse evolving point cloud of at least part of the environment, and a progressional deriving of a trajectory of movement. The method comprises a progressional matching of the sparse evolving point cloud with a known CAD-geometry, with a minimizing of a function configured to model a distance between the sparse point cloud and the known CAD-geometry and deriving a spatial localization and orientation of the surveying instrument. At least one surveying measurement value of the environment by a spatial measurement unit is combined with the sparse point cloud or the plan information.

Abstract: Surveying apparatus comprising an event-based camera comprising a dynamic vision sensor.

Abstract: One example method is disclosed that includes the steps of capturing a plurality of images of a scene, wherein each of the plurality of images of the scene captures a different perspective of a portion of an object; establishing a three-dimensional (“3D”) model of the object using at least some of the plurality of images of the scene; initializing a T-spline based at least in part on the 3D model; determining a first photometric error associated with the 3D model and the T-spline; and optimizing the T-spline based on the first photometric error to create an optimized T-spline.