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 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 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: 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 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 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.