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: The invention relates to a method for enhancing images for metrological applications. The method comprises the steps: 1) providing a geometric correction image having an image geometric correctness higher than the processed image geometric correctness and showing at least a part of the scene of interest, and 2) at least partially reducing the loss of initial metrological information in the distorted metrological information by fusing the enhanced image with the geometric correction image.

Abstract: A method for enhancing images for metrological applications. A first set of first images is provided, wherein the first set comprises at least one first image, the first set representing a scene of interest, and a second set of second images is provided, wherein the second set comprises at least one second image, the second set representing at least a part of the scene of interest. The method comprises the following steps: 1) jointly processing the first set and the second set by a neural network, and 2) outputting a third set of images by the neural network, the third set comprising at least one processed image, from which is determinable the position and/or orientation of the at least one object with a processed precision, wherein the processed precision is equal to or higher than the initial precision.

Abstract: Systems and methods for surveillance of a facility including facility elements. The system includes a central computing unit providing a digital model of the facility providing topological or logical or functional relationships of the facility elements, surveillance sensors adapted for surveillance of a plurality of the facility elements and for generation of surveillance data, communication means for transmitting data from the surveillance sensors to the central computing unit, and state derivation means configured to analyse the surveillance data and derive a state of a respective facility element. The central computing unit is configured to record a state pattern by combining states of at least one facility element based on at least one relationship of the facility element provided by the facility model, provide a state pattern critical-noncritical classification model which considers relationships provided by the facility model, and perform a criticality-classification based on the relationship.

Abstract: A monitoring system for locating and classifying an event in a monitoring area by a computation unit including a visual 3D capturing unit providing geometric 3D information and an acoustic capturing unit providing an acoustic information of the monitoring area. An event detector is configured with an acoustic channel and a visual channel to detect the event. The acoustic channel is configured to detect the event as a sound event in the acoustic information and to determine a localization of the sound. The visual channel is configured to detect the event as a visual event in the geometric 3D information and to derive a localization of the visual event. The event detector provides detected events with a region of interest for detected event, which is analyzed in order to assign the detected event a class within a plurality of event classes.

Abstract: A method of providing an augmented view of a real world scenery and of an occluded subsurface infrastructure. An image is taken by a camera with an image sensor and image reference information comprising a camera position and a camera orientation. From three dimensional information of a subsurface infrastructure, a two dimensional projection on the image sensor is made by using the reference information. A projection position of an anchor element of the subsurface infrastructure being visible on the at least one image is compared with an image position of the anchor element. A difference between the image position and the projection position is compensated for matching and overlaying the two dimensional projection derived from the three dimensional information of the subsurface infrastructure with the at least one image and thereby providing an improved augmented view.

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 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: An Augmented Reality (AR)-device, including a visual sensor for capturing an environment of the AR-device, a display providing a real view of the environment, and overlays onto the real view according to AR-data including at least one of design data and measured data, a computer for reading and controlling the visual sensor, at least one of receiving, generating and storing the AR-data, and identification features which are assigned to each of a plurality of reference systems, generating the overlays, establishing a referenced status of the AR-device relative to each of the reference systems by identifying a reference system based on at least one identification feature captured by the visual sensor, determining a pose of the AR-device relative to the identified reference system, and maintaining the referenced status in case of loss of visual contact between the visual sensor and the identification feature, based on a Visual Localisation and Mapping (VSLAM)-process.

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 image-based point measurement includes moving a surveying system along a path through a surrounding and capturing a series of images of the surrounding. A subset of images are defined as frames and a subset of frames are defined as key-frames. Textures are identified in first and second frames and are tracked in successive frames to generate first and second frame feature lists. A structure from motion algorithm is used to calculate camera poses for the images based on the first and second frame feature lists. Corresponding image points in images of the series of images are identified using feature recognition in at least a plurality of images. Three-dimensional coordinates of the selected image point are determined using forward intersection with the poses of the subset of images in which corresponding image points are identified. The three-dimensional coordinates of the selected image point are presented to the user.

Abstract: An Augmented Reality (AR)-device, including a visual sensor configured for capturing an environment of the AR device, a display configured for providing a real view of the environment, and overlays onto the real view according to AR-data, wherein the AR data are spatially linked to a reference system and comprise designed data, measured data, and remeasurement indications, a computer configured for reading and controlling the visual sensor, determining a pose of the AR-device relative to the reference system, at least one of receiving, generating and storing the AR-data, and generating the overlays. The remeasurement indications are based on an evaluation of the measured data, and spatially linked to the reference system at corresponding locations of the environment where the measured data lack a target quality.

Abstract: One aspect of the invention relates to a fully automatic method for calculating the current, geo-referenced position and alignment of a terrestrial scan-surveying device in situ on the basis of a current panoramic image recorded by the surveying device and at least one stored, geo-referenced 3D scan panoramic image.

Abstract: A method and system for surveying and/or metrology for assigning particular classes of interest within measurement data, wherein an assignment of at least one measurement object to a first class of interest within the measurement data based on a classification model, is processed by a feedback procedure providing feedback data for a training procedure which provides update information for the classification model, wherein the training procedure is based on a machine learning algorithm, e.g. relying on deep learning for supervised learning and/or unsupervised learning.

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: The invention generally relates to an industrial or geodetic surveying device having a tracking unit configured to receive over a tracking channel a tracking signal which is used to track a cooperative target. According to the invention, the surveying device comprises a camera to generate image data, wherein based on the additional knowledge about the position of the cooperative target in an image generated in the locked state, the visual appearance of the target carrier is learned and the result is stored in the form of a detector for use in a backup tracking mode.