Embodiments relate to methods for efficiently encoding sensor data captured by an autonomous vehicle and building a high definition map using the encoded sensor data. The sensor data can be LiDAR data which is expressed as multiple image representations. Image representations that include important LiDAR data undergo a lossless compression while image representations that include LiDAR data that is more error-tolerant undergo a lossy compression. Therefore, the compressed sensor data can be transmitted to an online system for building a high definition map. When building a high definition map, entities, such as road signs and road lines, are constructed such that when encoded and compressed, the high definition map consumes less storage space. The positions of entities are expressed in relation to a reference centerline in the high definition map. Therefore, each position of an entity can be expressed in fewer numerical digits in comparison to conventional methods.

Described are a system (200) and method arranged to provide improved geocoded reference data to a 3D map representation. The system comprises a storage (201) having stored thereupon a 3D map representation comprising a textured 3D representation provided with geocoded reference data and formed based on imagery, the imagery being associated to information relating to at least one imaging device which has captured the imaging. The system comprises further a processor (208) arranged to receive at least one new image associated to information related to an imaging device which has captured the new image, perform registration of the new image to the 3D map representation, determine corresponding points in the new image and the 3D map representation, and determine displacement data for a plurality of 3D positions in the 3D map representation based on the determined corresponding points in the new image and the 3D map representation.

An imaging survey platform utilizes imaging sensors arranged in one or more arcs to capture nadir and oblique views as required for photogrammetric processing into image maps and 3D surface maps, where a common primary lens subsystem is used by sensors within an arc. The primary lens subsystem can project onto a curved (e.g., spherical) surface rather than onto a planar surface. This solves a limiting first order optical problem for airborne or spaceborne image capture. To fill missing data between sensors edges on an arc, a second and offset arc of sensors or a scanning mirror in front of the primary mirror system can be used. Each imaging sensor can be mounted on and controlled by its own computer, with this subsystem in turn may be mounted onto the arc using piezoelectric actuators to fine tune alignment image sensor relative to the primary lens subsystem.

Integrated Visual Geo-referencing Target Unit ABSTRACT A georeferencing target unit including: a generally planar top surface including a visual marker structure on the top surface, dimensioned to be observable at a distance by a remote visual capture device; an internal GPS tracking unit tracking the current position of the target unit; a microcontroller and storage means for storing GPS tracking data; and wireless network interconnection unit for interconnecting wirelessly with an external network for the downloading of stored GPS tracking data; a power supply for driving the GPS tracking unit, microcontroller, storage and wireless network interconnection unit, a user interface including an activation mechanism for activating the internal GPS tracking unit to track the current position of the target unit over an extended time frame and store the tracked GPS tracking data in the storage means.

An apparatus for providing drone data provides a method of matching a user who needs drone data of a certain area with at least one provider capable of providing drone data of a part or the entirety of the certain area.

A scanner that can detect types of targets in a scan are includes a processor, housing and a 3D scanner disposed within the housing. The 3D scanner has a light source, a beam steering unit, a first angle measuring device, a second angle measuring device, and a light receiver, the beam steering unit cooperating with the light source and light receiver to define a scan area, the light source and the light receiver configured to cooperate with the processor system to determine locations a plurality of points in the scan area. In cases where the targets are spheres, the processor is configured to: identify potential sphere center points in the scan area by processing points identified in a single scan line; record locations of potential sphere center points; and compare some or all of the recorded locations to one another to select a sphere center point.

An imaging system can include a first and second camera configured to capture first and second sets of oblique images along first and second scan paths, respectively, on an object area. A drive is coupled to a scanning mirror structure, having at least one mirror surface, and configured to rotate the structure about a scan axis based on a scan angle. The first and second cameras each have an optical axis set at an oblique angle to the scan axis and include a respective lens to focus first and second imaging beams reflected from the mirror surface to an image sensor located in each of the cameras. The first and second imaging beams captured by their respective cameras can vary according to the scan angle. Each of the image sensors captures respective sets of oblique images by sampling the imaging beams at first and second values of the scan angle.

Methods and apparatus to count people are disclosed. Example apparatus disclosed herein are to populate a list with first characteristic datasets obtained from a first plurality of images, respective ones of the first characteristic datasets representative of corresponding faces. Disclosed apparatus are also to perform comparisons of the first characteristic datasets to each other to determine a first number of unique faces, the comparisons limited to the first characteristic datasets obtained during the first period of time. Disclosed apparatus are further to delete the first characteristic datasets from the list after the first period of time has ended, and re-populate the list with second characteristic datasets obtained from a second plurality of images representative of the environment during a second period of time of the media presentation, the second period of time subsequent to the first period of time.

A system and method of detecting subsurface karst features includes receiving surface mapping data. A potential surface pad location can be identified in view of the surface mapping data. A resistivity survey for the potential surface pad location can be designed. The resistivity survey can include at least one long line extending through a surface hole for each of one or more wellbores in the potential surface pad location, and a short line extending through the surface hole of one of the one or more wellbores, each short line intersecting the long line substantially at the surface hole of one of the one or more wellbores. High resistivity areas exceeding approximately 150 Ohm per meter can be identified as sub surface karst features within the resistivity survey.

Disclosed is a system and method for infrastructure inspection, comprising means for generating a 3D model of a specific piece of infrastructure, such as a LIDAR or photogrammetric sensor on board a helicopter or UAV, the model acting as a basis for creating a waypoint sequence according to which a route will be programmed, which will later be followed by vehicles for inspecting the piece of infrastructure. The vehicles are preferably multi-rotor UAVs that carry out their inspection by gathering data without a LIDAR sensor and which, when performing their programmed route, will be able to dispense with complex on-board electronic processing equipment, all of which results in greater flight autonomy.