A Position and Orientation Measurement Engine (POME) is a mobile camera system that can be used for accurate indoor measurement (e.g., at a construction site). The POME uses a plurality of cameras to acquire images of a plurality of targets. If locations of the plurality of targets are precisely known, images of the targets can be used to determine a position of the POME in relation to the plurality of targets. However, to precisely determine locations of the plurality of targets can be time consuming and/or use expensive equipment. This disclosure discusses how to use a camera system with an electronic distance measuring unit to determine locations of the plurality of targets.

A Position and Orientation Measurement Engine (POME) is a mobile camera system that can be used for accurate indoor measurement (e.g., at a construction site). The POME uses a plurality of cameras to acquire images of a plurality of targets. If locations of the plurality of targets are precisely known, images of the targets can be used to determine a position of the POME in relation to the plurality of targets. However, to precisely determine locations of the plurality of targets can be time consuming and/or use expensive equipment. This disclosure discusses how to use a camera system with an electronic distance measuring unit to determine locations of the plurality of targets.

A position measurement system includes: an image data acquisition unit that acquires first image data photographed by a first camera of a first stereo camera provided at a work machine and second image data photographed by a second camera of the first stereo camera; a stereo measurement unit that executes stereo measurement on the basis of the first image data, the second image data, and parameters related to the first camera and the second camera; a first adjustment unit that changes at least a part of the parameters to adjust a stereo ratio of first disparity image data subjected to stereo measurement; and a second adjustment unit that changes at least a part of the parameters to adjust a scale of first three-dimensional data obtained from the first disparity image data.

A Position and Orientation Measurement Engine (POME) is a mobile camera system that can be used for accurate indoor measurement (e.g., at a construction site). The POME uses a plurality of cameras to acquire images of a plurality of targets. If locations of the plurality of targets are precisely known, images of the targets can be used to determine a position of the POME in relation to the plurality of targets. However, to precisely determine locations of the plurality of targets can be time consuming and/or use expensive equipment. This disclosure discusses how to use a camera system with an electronic distance measuring unit to determine locations of the plurality of targets.

A Position and Orientation Measurement Engine (POME) is a mobile camera system that can be used for accurate indoor measurement (e.g., at a construction site). The POME uses a plurality of cameras to acquire images of a plurality of targets. If locations of the plurality of targets are precisely known, images of the targets can be used to determine a position of the POME in relation to the plurality of targets. However, to precisely determine locations of the plurality of targets can be time consuming and/or use expensive equipment. This disclosure discusses how to use a camera system with an electronic distance measuring unit to determine locations of the plurality of targets.

A method for measuring distance using an unmanned aerial vehicle (UAV) includes: identifying a target object to be measured; receiving a plurality of images captured by a camera of the UAV when the UAV is moving and the camera is tracking the target object; collecting movement information of the UAV corresponding to capturing moments of the plurality of images; and calculating a distance between the target object and the UAV based on the movement information and the plurality of images.

A method for detecting a displacement of a mobile platform includes acquiring a first frame and a second frame using an imaging device coupled to the mobile platform, obtaining an angle of the imaging device relative to a reference level while acquiring the first frame, and determining the displacement of the mobile platform based at least on the first frame, the second frame, and the angle of the imaging device relative to the reference level.

A method for detecting a displacement of a mobile platform includes acquiring a first frame and a second frame using an imaging device coupled to the mobile platform, obtaining an angle of the imaging device relative to a reference level while acquiring the first frame, and determining the displacement of the mobile platform based at least on the first frame, the second frame, and the angle of the imaging device relative to the reference level.

An unmanned aerial vehicle calibration method and system based on a color 3D calibration object. The method comprises: placing a color chequerboard 3D calibration object in a scene to be photographed; using an unmanned aerial vehicle to photograph images of the color chequerboard 3D calibration object from at least three different orientations; using a vanishing point theory to linearly solve the internal parameters of a camera of the unmanned aerial vehicle according to the photographed images of the color chequerboard 3D calibration object; and using a coordinate projection transformation method to determine a geometric constraint relationship between a spatial position and the images of the camera of the unmanned aerial vehicle according to the internal parameters of the camera of the unmanned aerial vehicle.

An unmanned aerial vehicle calibration method and system based on a color 3D calibration object. The method comprises: placing a color chequerboard 3D calibration object in a scene to be photographed; using an unmanned aerial vehicle to photograph images of the color chequerboard 3D calibration object from at least three different orientations; using a vanishing point theory to linearly solve the internal parameters of a camera of the unmanned aerial vehicle according to the photographed images of the color chequerboard 3D calibration object; and using a coordinate projection transformation method to determine a geometric constraint relationship between a spatial position and the images of the camera of the unmanned aerial vehicle according to the internal parameters of the camera of the unmanned aerial vehicle.