Abstract: A method for registering two or more three-dimensional (3D) point clouds. The method includes, with a surveying instrument, obtaining a first 3D point cloud of a first setting at a first position, initiating a first Simultaneous Localisation and Mapping (SLAM) process by capturing first initial image data at the first position with a camera unit comprised by the surveying instrument, wherein the first initial image data and the first 3D point cloud share a first overlap, finalising the first SLAM process at the second position by capturing first final image data with the camera unit, wherein the first final image data are comprised by the first image data, with the surveying instrument, obtaining a second 3D point cloud of a second setting at the second position, and based on the first SLAM process, registering the first 3D point cloud and the second 3D point cloud relative to each other.

Abstract: A method of generating an information enhanced model of an industrial plant. The method includes providing a first digitalized topology of a plant by processing a spatial scan of the plant, wherein in course of the processing, plant structural elements and their interconnections are recognized and digitalized, providing a second digitalized topology of the plant, based on a process and instrumentation diagram, the second topology being representative of plant structural elements and their interconnections, and correlating the first and the second digitalized topology by at least semi-automatically identifying and interlinking corresponding structural elements in the first and second digitalized topology.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: A method may include identifying features in images of a setting captured by cameras associated with a laser scanner at a first location. The features may correspond to elements in the setting. The method may include correlating the features with scan point data associated with the elements. The scan point data may be derived from a scan of the setting by a laser of the laser scanner at the first location. The method may include tracking the features within images captured by the cameras. The images may be captured during movement of the laser scanner away from the first location. The method may include estimating a position and/or an orientation of the laser scanner at a second location based on the tracking of the features and based on the correlating of the features with the scan point data.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: An Augmented Reality (AR)-system comprising a permanent marker having a defined pose relative to a coordinate system, an AR-device having a camera and a processing unit, wherein the AR-device is configured to visually detect and identify the permanent marker, determine a relative pose between the AR-device and the permanent marker, a temporary marker having a coded design and an undefined pose relative to the coordinate system and the permanent marker, wherein the AR-device is configured to visually detect and identify the temporary marker by the coded design, determine a relative pose between the permanent marker and the temporary marker, based on the determined relative pose between the permanent marker and the temporary marker, defining a pose of the temporary marker relative to the coordinate system, determine a relative pose between the AR-device and the temporary marker.

Abstract: A method for automatic surveying of a real word object by a surveying or metrology instrument. It comprises an acquiring of a picture by the surveying or metrology instrument, which picture is comprising the real world object to be surveyed, and an automatic detecting and classifying of the detected real world object to be surveyed in the picture, and also an automatic surveying of the detected real world object by the surveying or metrology instrument for determining a location and/or a geometrical property of the real world object. The automatic detecting and classifying is done with a classifier based on data acquired by machine learning, which machine learning is based on machine learning training data derived from a virtual digital 3d-model which is representing the real world object and which comprises meta information of this 3d-model.

Abstract: A volume determining method for an object on a construction site is disclosed. The method may include moving a mobile camera along a path around the object while orienting the camera repeatedly onto the object. The method may include capturing a series of images of the object from different points on the path and with different orientations with the camera, the series being represented by an image data set; performing a structure from motion evaluation with a defined algorithm using the series of images and generating a spatial representation; scaling the spatial representation with help of given information about a known absolute reference regarding scale; defining a ground surface for the object and applying it onto the spatial representation; and calculating and outputting the absolute volume of the object based on the scaled spatial representation and the defined ground surface.

Abstract: A method for a three dimensional surveying of a 3D-scene for deriving a true-to-size 3D-model. It involves deriving a first 3D-partial-model of a section of the 3D-scene together with a capturing of at least one first 2D-visual-image and a second 3D-partial-model of another section of the 3D-scene, together with a capturing of at least one second 2D-visual-image, wherein the 3D-partial-models are partially overlapping. The first 3D-partial-model is conglomerated with the second 3D-partial-model to form the 3D-model of the 3D-scene, which is done with defining a first line segment in the first 2D-visual-image and a second line segment in the second 2D-visual-image, which first and second line segments are representing a visual feature, which is common in both of the 2D-visual-images. The line segments in the 2D-visual-images are utilized in conglomerating the corresponding 3D-partial models to form the 3D-model of the whole 3D-scene.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.

Abstract: A surveying system for surveying and tracking a movable target object that defines a target point includes a surveying device with a sighting unit defining a target axis and a detector for generating a continuously current amount-of-deviation signal dependent on a deviation from an optimal target orientation. A second unit on the target object side enables continuous determination of movements and/or positions of the target object with reference to an external coordinate system. The surveying system includes a target point tracking mode in which respective first measurement data currently generated by the first unit and the respective current amount-of-deviation signal and respective second measurement data currently generated by the second unit are continuously aggregated. On the basis thereof, a control signal is derived for continuous automatic motorized modification of the target axis orientation such that the target axis continuously aims at the target point.

Abstract: A system is disclosed that comprises a camera module and a control and evaluation unit. The camera module is designed to be attached to the surveying pole and comprises at least one camera for capturing images. The control and evaluation unit has stored a program with program code so as to control and execute a functionality in which a series of images of the surrounding is captured with the at least one camera; a SLAM-evaluation with a defined algorithm using the series of images is performed, wherein a reference point field is built up and poses for the captured images are determined; and, based on the determined poses, a point cloud comprising 3D-positions of points of the surrounding can be computed by forward intersection using the series of images, particularly by using dense matching algorithm.