1581 results about "Ir camera" patented technology

The invention discloses a historical block scene three-dimensional reconstruction method and system based on Gaussian sputtering, and the method comprises the steps: collecting a historical block video sequence through a lightweight panorama camera, extracting a multi-frame panorama, and generating an image data set through a projection converter; monocular depth and normal estimation is carried out through a pre-training visual model, and a prior depth and normal graph data set of a historical block scene is constructed; sparse reconstruction is carried out on the multi-view image data set based on the SfM technology, initial point cloud and camera pose information are acquired, and a Gaussian ellipsoid is optimized in combination with prior depth and normal information; dynamically calculating the geometric width estimation value of the street, and guiding and adjusting the adaptive density of the Gaussian ellipsoids of the vertical surfaces on the two sides; rendering the optimized Gaussian ellipsoid through an improved rasterization renderer; and designing a multi-modal loss function and a regularization mechanism to optimize reconstruction and rendering results. According to the method, high-fidelity three-dimensional reconstruction of the historical block scene is realized, and the adaptability of the Gaussian sputtering method to the complex block scene is enhanced.

The invention provides a moving target capturing method and system based on AI multi-view vision, and relates to the technical field of data processing.The method comprises the steps that camera parameters in all vision systems are calibrated, and the camera parameters comprise a camera internal parameter matrix and a camera external parameter matrix; extracting 2D feature points of the moving target through each calibrated visual system; reconstructing each 2D feature point by combining a multi-view geometric reconstruction algorithm and a least square method according to the calibrated camera parameters to obtain 3D feature points; constraints are added to the 3D feature points, and the constraints comprise spatial constraints, direction vector constraints and time sequence constraints; reconstructing the 3D feature points added with the constraints through a multi-view geometric analysis algorithm to obtain three-dimensional motion information of the moving target; and outputting the three-dimensional motion information of the moving target to complete the capture of the moving target. And non-contact high-precision capture of the moving target can be realized.

The invention discloses a three-dimensional scene reconstruction method, electronic equipment, a storage medium and a program product, and relates to the technical field of data processing, and the method comprises the steps: inputting each frame of multi-view image into a depth model, and obtaining a prediction depth map of each frame of multi-view image; for any target frame image in each frame of multi-view image, optimizing a local 3D Gaussian model and camera attitude information of the target frame image based on the predicted depth map of the target frame image and the depth information of the previous frame image to obtain an updated local 3D Gaussian model and updated camera attitude information of the target frame image; and optimizing the global 3D Gaussian model to obtain an updated global 3D Gaussian model based on the updated local 3D Gaussian model and the updated camera attitude information of each frame of multi-view image, and performing three-dimensional scene reconstruction based on the updated global 3D Gaussian model. According to the invention, the accuracy of a view synthesis result based on three-dimensional scene reconstruction is improved.

An electronic door system includes a door frame, a door hingedly coupled to the door frame, an electronic locking mechanism coupled to the door, one or more lights coupled to the door frame, a camera system including at least two of a camera, a proximity or motion sensor, or a doorbell, and a wiring harness extending through the door frame and the door. The wiring harness is coupled to the electronic locking mechanism, the one or more lights, and the camera system. The wiring harness is configured to electrically couple to an external power source.

The invention relates to the technical field of motion capture data processing, and discloses a robot reinforcement learning model construction method based on optical inertial fusion whole body motion capture, and the method comprises the steps: measuring and recording a plurality of key parameters of a target human body; carrying out primary calibration and recording on all inertial sensors worn on a target human body, and calibrating all cameras arranged around at the same time; in the process that the target human body executes the specified action, synchronously acquiring action sampling data of the target human body; the action sampling data comprises motion data corresponding to the inertial sensor and camera image data corresponding to the camera; the motion data and the camera image data are processed, fused and optimized, and optimized joint posture quaternary data and human body motion sequence data are obtained; and inputting the human body action sequence data into the reinforcement learning model of the humanoid robot, and configuring the preset reward function to perform reinforcement learning training, so that the learning efficiency of the robot and the accuracy of action execution can be improved.

The invention discloses a porcelain bushing power transformation equipment surface modeling method based on an unmanned aerial vehicle and light three-dimensional Gaussian, and the method comprises the steps: determining an unmanned aerial vehicle inspection task route, shooting porcelain bushing power transformation equipment through the unmanned aerial vehicle in a multi-view manner, obtaining an equipment image set, carrying out the noise reduction processing of the equipment image set, and carrying out the camera pose estimation. Obtaining surface depth information of the equipment image set based on an SDF function; dense point clouds are generated based on the equipment images and the corresponding camera pose information, three-dimensional Gaussian is constructed according to the dense point clouds, and rendered images are obtained; compressing the three-dimensional Gaussian through a light Gaussian method; establishing a neural implicit surface reconstruction model; constructing a composite loss function, and training and optimizing the reconstruction model based on the composite loss function; according to the method, the lightweight Gaussian compression technology is introduced into the implicit surface reconstruction method, efficient compression and rapid rendering of the scene are achieved, the storage requirement is remarkably reduced, and the modeling precision of the equipment surface and the capturing capacity of complex surface details are improved.

The invention provides an infrared scene reconstruction and rendering method and device based on three-dimensional Gaussian splashing, and the method comprises the steps: carrying out the processing of preprocessed infrared image data through employing an SfM algorithm, obtaining a sparse three-dimensional point cloud and a camera pose, and setting a Gaussian ellipsoid at the center position of the sparse three-dimensional point cloud, so as to construct a three-dimensional Gaussian point cloud model; inputting the camera pose into a Gaussian microrasterized renderer to render the three-dimensional Gaussian point cloud model to obtain a two-dimensional image of a corresponding view angle; the two-dimensional image and the infrared image data of the camera pose are compared through a loss function, the model is trained, a trained three-dimensional Gaussian point cloud model is obtained, and the loss function comprises a temperature gradient field, the projection position of a Gaussian ellipsoid in a pixel plane under the current camera visual angle and the main axis projection direction; and processing the trained three-dimensional Gaussian point cloud model by using a three-dimensional graphic engine and a 3D Gaussian rasterization renderer to obtain an infrared simulation image. And the authenticity of reconstruction and rendering of the infrared scene is relatively high.

The invention provides a space three-dimensional target detection method, device and equipment and a storage medium, and aims to unify an infrared image and point cloud data in a BEV space and solve the problem of difference between data structure representation of different sensors and a space coordinate system; point cloud depth supervision and camera parameter priori are introduced into a camera branch to enhance the depth estimation capability of the camera branch, different branches are fused, and fused features and different branches are detected, so that the accuracy of subsequent target detection is improved.

An apparatus comprises an interface and a processor. The interface may be configured to receive pixel data representing a first field of view of a camera and four-dimensional (4D) point cloud data representing a second field of view of a 4D imaging radar sensor. The first field of view of the camera and the second field of view of the 4D imaging radar sensor generally overlap. The processor may be configured to process the pixel data and the 4D point cloud data arranged as video frames and perform an extrinsic parameter calibration for the 4D imaging radar sensor and the camera based on adaptive projection error. The extrinsic parameter calibration may comprise applying a pose calibration process to the video frames. The pose calibration process may use (i) a respective translate vector and a respective rotation matrix for each of the 4D imaging radar sensor and the camera and (ii) a radar corner reflector to obtain configuration parameters for the first field of view of the camera and the second field of view of the 4D imaging radar sensor. The pose calibration process generally comprises capturing data for a plurality of positions of the radar corner reflector between a near-distance value and a long-distance value, and modifying a scale of a projection error of the radar corner reflector based on a size of the radar corner reflector in an image captured by the camera.

A method, for determining a dynamic occupancy grid, includes: obtaining radar measurement data from at least one radar sensor of an apparatus; obtaining camera-derived data based on at least one image obtained by at least one camera of the apparatus; and determining the dynamic occupancy grid based on the radar measurement data and the camera-derived data.

The present application discloses a displacement sensing apparatus and displacement sensing method for a building structure, and a storage medium. The displacement sensing apparatus comprises: a fixing module comprising a fixing base and a fixing support, wherein the fixing base is configured to be coupled with a monitoring point for a structure under measurement to form a whole structure; and a projection module and a camera module, wherein the camera module is arranged in front of the projection module by means of the fixing support at an angle perpendicular to the field of view, and is configured to collect a laser image formed on the projection module by a laser emission module which is provided at a fixed point.

The invention provides a robot indoor navigation method and system, and the method comprises the steps: obtaining an RGB image frame sequence collected by a camera, and estimating a camera pose and a sparse three-dimensional landmark point of an image frame through a depth block visual odometer; based on the camera pose and the sparse three-dimensional landmark point, dense geometric enhancement is carried out on the image frame through a deep neural network of a transformer architecture to obtain dense geometric prior information; training a neural radiation field according to the initial camera pose, the dense geometric prior information and the image frame data, and performing joint optimization on neural radiation field parameters and the camera pose based on luminosity consistency, geometric consistency and camera pose constraints; based on image frames collected in real time, novel view synthesis is carried out through the optimized nerve radiation field, and robot navigation is carried out based on a novel view. According to the scheme, accurate estimation of the camera pose and high-quality reconstruction of the three-dimensional scene can be realized, the computing resource overhead is low, and the real-time performance can be guaranteed.

The invention discloses silicon optical wafer testing equipment and an optical fiber pose adjusting mechanism, method and system thereof. The optical fiber pose adjusting mechanism comprises a camera assembly and a deflection optical path assembly. The probe station is used for bearing a silicon optical wafer; an optical fiber coupling module; when the driving assembly drives the silicon optical wafer to be located in the imaging view field of the camera assembly, the camera assembly is adjusted to enable the coordinate system to be parallel to the cutting channel of the silicon optical wafer; when the driving assembly drives the deflection optical path assembly to move into an imaging view field of the camera assembly, the camera assembly collects lateral images of the end part of the optical fiber in at least two different directions through the deflection optical path assembly; and the optical fiber coupling module is used for performing pose adjustment on the end part of the optical fiber according to the lateral image and the direction of the coordinate system of the camera assembly, so that the end part of the optical fiber is preliminarily aligned with the silicon optical wafer. The operation difficulty and the equipment structure of alignment coupling between the optical fiber end part and the silicon optical waveguide are simplified, and the equipment cost is reduced.

The present invention relates to a mobile phone protective case with a rotating support, where the protective case includes a main body and a camera support assembly, the main body is provided with an accommodation cavity for accommodating a mobile phone, the camera support assembly is removably installed at a camera hole, the camera support assembly includes an installation base and a support, the support is rotationally connected to the installation base through a hinge, the support is configured to protect a camera of the mobile phone when closed, and the support is configured to support the mobile phone when opened.

The invention discloses a turntable-based dual confocal image scanning microscope and an imaging method, and relates to the technical field of optical elements, systems, instruments and imaging. The imaging light source assembly, the optical fiber transmission assembly, the light source collimation assembly, the structured light generation assembly, the turntable assembly, the microscopic amplification assembly and the camera detection assembly are arranged along a light path; the structured light generation module realizes structured light illumination on a sample surface by loading a specific mask sequence, super-resolution imaging is realized, pinholes in the turntable assembly are equidistantly arranged according to an Archimedes spiral, and the turntable assembly rotates at a high speed to realize multi-point parallel scanning and de-scanning; the detection module performs detection by using an area array detector, so that the resolution improvement of double diffraction limit is realized; according to the dynamic pinhole array-pixel redistribution method, super-resolution reconstruction is carried out based on an image scanning microscopic system principle, and Stokes shift, optical aberration and other non-ideal conditions can be effectively corrected.

Disclosed in the present invention is a photometric stereo-based device for rapidly detecting surface features of an object, capable of rapidly acquiring a plurality of images meeting the requirements of a photometric stereo algorithm. The device comprises a light emitting assembly, an acquisition assembly located above the light emitting assembly, and a data processing module; the acquisition assembly comprises a light path system and a camera group; the light path system comprises: a beam splitting prism group used for splitting reflected light from the surface of an object into a plurality of beams of light and respectively outputting the plurality of beams of light in different preset directions to form images to be processed, and a plurality of bandpass filters correspondingly arranged on the output sides of the plurality of beams of light used for forming said images, wherein the central wavelengths of the bandpass filters are respectively configured to be different wavebands of the reflected light from the surface of the object; the camera group comprises a plurality of cameras which are arranged behind the bandpass filters in a one-to-one correspondence mode and acquire filtered light beams; and the data processing module receives image information sent by the cameras, and performs compensation and photometric stereo reconstruction on the image information, so as to obtain surface features of the object. Further disclosed is a method implemented on the basis of the device.

The invention discloses an underwater environment three-dimensional reconstruction method, device and equipment and a storage medium, and relates to the technical field of underwater robots, and the underwater environment three-dimensional reconstruction method comprises the steps: transmitting laser to a target object, and collecting a laser reflection image; extracting pixel coordinates of laser stripes from the laser reflection image; calculating a three-dimensional space coordinate of the laser point based on the pixel coordinate and a camera internal reference matrix; generating a control instruction according to the depth information of the three-dimensional space coordinates, and sending the control instruction to an underwater vehicle to enable the underwater vehicle to execute equidistant diameter circular motion and collect and feed back three-dimensional point cloud data under different poses; and fusing the three-dimensional point cloud data under different poses to obtain a target three-dimensional point cloud model, and completing three-dimensional reconstruction. According to the invention, three-dimensional reconstruction of the underwater environment can be efficiently and accurately realized at low cost, and powerful technical support is provided for underwater exploration and scientific research.

Monitoring and control system and method for additive manufacturing an in-situ macro-field thermography that uses an IR camera or near-IR camera to prioritize the data captured from an entire print layer, processes data streams layer-by-layer, and provides thermal history of previously printed layers as feedback to the control system. The system leverages one or more different mathematical thermophysical-based (MTB) models to compute a thermally related specification in order to optimize the printing sequence of islands or stripes layer-by-layer. The thermal feedback from the thermography system calibrates or updates the thermal model layer-by-layer. The system and / or method may provide real-time optimization of scanning topology in chessboard and stripe printing strategies. The method may be implemented by one or more computer programs controlling one or more computer controllers of an additive manufacturing system, such as a 3D printer implementing a metal powder bed fusion additive manufacturing process.

The invention discloses a to-be-detected object surface image acquisition device, an image selection method and a defect detection method. The to-be-detected object surface image acquisition device comprises a projector, a diffusion plate, a reflector and a camera. The projector is suitable for projecting stripes; the diffusion plate is suitable for diffusing fringes projected by the projector to the surface of the to-be-measured object; the reflector moves between a first position and a second position relative to the to-be-measured object, and at the first position, the reflector shields a light path from the projector to the diffusion plate. And at the second position, the reflecting mirror avoids a light path from the projector to the diffusion plate. The camera is suitable for receiving a signal reflected by the surface of the to-be-measured object after the diffusion plate enters the surface of the to-be-measured object so as to obtain a phase deflection technology (PMD) image, or receiving a signal diffused by the surface of the to-be-measured object after the reflection mirror enters the surface of the to-be-measured object so as to obtain a fringe projection profile measurement (FPP) image. A phase deflection technology and a fringe projection profile measurement technology are fused in one set of defect detection system, rapid switching of two three-dimensional measurement defect detection technologies is realized for products with complex materials and different surface roughness, and the defect detection system is ensured to be high in efficiency, high in detection capability, wide in applicability and high in detection rate.

The invention discloses a narrow space spraying trajectory planning method based on reinforcement learning, and the method comprises the steps: obtaining environment data through a LiDAR camera and a TOF camera, and obtaining a LiDAR point cloud and a TOF point cloud; carrying out registration fusion on the LiDAR point cloud and the TOF point cloud, and carrying out normal vector unification processing on each point of the fused point cloud; reconstructing by introducing a Poisson equation improved by shielding perception weight, and eliminating noise through Laplacian smoothing processing to obtain a target point cloud set; designing a state space, an action space and a reward function of reinforcement learning according to the planning of the spraying path trajectory, and determining a spraying path trajectory planning strategy; and based on the target point cloud set, adopting a spraying path trajectory planning strategy to carry out spraying trajectory planning. Sensor data fusion is realized through an improved iterative nearest point algorithm, and a shielding area is repaired in cooperation with a Poisson reconstruction algorithm, so that accurate correspondence between input parameters and output film thickness can be realized, and the control precision of the spraying thickness is remarkably improved.

Systems, methods, and apparatuses are described for causing a camera of a head-mounted computing device to capture a first video, the head-mounted computing device comprising a camera direction control element for controlling a capture direction of the camera, and a camera zoom control element for controlling zoom of the camera. One or more objects in the captured first video may be identified based on a detected gaze angle of a user wearing the head-mounted computing device. A target location in an environment may be determined, and based on such target location, the capture direction and zoom of the camera may be adjusted using the camera direction control element and the camera zoom control element, respectively. The camera may capture, based on the adjusted capture direction and the adjusted zoom of the camera, a second video using the camera of the head-mounted computing device.

The invention relates to the technical field of automatic driving perception, and discloses a pre-fusion detection method and system for depth estimation optimization, a vehicle and a medium, and the method comprises the steps: obtaining point cloud data of a laser radar and image data of a camera, carrying out the preprocessing of the point cloud data and the image data, and correspondingly obtaining point cloud features and image features; performing depth optimization on the image features to obtain depth image features; the depth image features are input into a trained depth estimation network, a depth prediction result is obtained, and the depth estimation network is obtained by supervising and training the image data of the camera according to the point cloud data of the laser radar; and determining aerial view features according to a depth prediction result, and performing feature fusion on the aerial view features and the point cloud features to obtain fusion features for target detection. The method can achieve the deep optimization of the image features, and further improves the depth estimation precision and the overall performance of target detection through combining with the depth estimation network obtained through supervised training.

The invention discloses a three-dimensional point cloud reconstruction method and device based on a Gaussian splash algorithm, and a medium, and relates to the technical field of three-dimensional point cloud reconstruction, and the method comprises the steps: obtaining a plurality of images; inputting the plurality of images into a pre-trained VGGT model to obtain DPT features obtained by feature coding output by a VIT encoder based on the VGGT model, and camera parameters and global point cloud data output by the VGGT model; based on the DPT features, the camera parameters and the global point cloud data, obtaining Gaussian splashing parameters corresponding to each pixel position of each image; and obtaining target three-dimensional point cloud data based on the Gaussian ball position increment in the Gaussian splashing parameters and the local point cloud data under the camera coordinates. The method is used for solving the problem that in the prior art, when multi-view three-dimensional point cloud reconstruction is carried out, the difference between simulation and a real object is large, and the difference between simulation and the real object is reduced.

The invention discloses a three-dimensional Gaussian splash initialization fault-tolerant enhancement method and system based on dynamic noise disturbance, a terminal and a storage medium, and the method comprises the steps: collecting each visual angle scene image containing a to-be-reconstructed scene, and determining a camera pose according to each visual angle scene image, constructing a data set required by a training model according to each view scene image and the camera pose; generating a random point cloud as an initial point cloud, inputting the initial point cloud into a three-dimensional Gaussian splash model, and inputting the training set to train the three-dimensional Gaussian splash model; and inputting any new camera pose into the trained three-dimensional Gaussian splash model, and rendering and outputting a scene image at a corresponding view angle. According to the method, the sensitivity of the model to initialization conditions is reduced through a systematic noise injection mechanism, high-precision reconstruction in a random initialization scene is realized, and the final reconstruction effect of the 3DGS is greatly improved.

The invention provides a phase-locked amplification system for enhancing the signal-to-noise ratio of ultrafast laser pumping-detection transient imaging. The system comprises a signal input module which is arranged on a pumping light path and a detection light path, wherein the signal input module comprises a light splitting plain film and an imaging objective lens which are arranged in sequence, wherein the centers of the light splitting plain film and the imaging objective lens are located on a first axis; the centers of the first reflector, the filter, the focusing lens and the camera are located on a second axis in sequence, and the camera is used for shooting light reflected by the sample to obtain a first signal; the reference acquisition module comprises a beam splitting piece and a second reflecting mirror, the beam splitting piece is arranged on the pumping light path, and a reference light path is shot through a camera to obtain a second signal; and the phase-sensitive detection module is used for calculating the first signal and the second signal to obtain a carrier distribution condition at a preset moment. According to the invention, low pumping measurement is realized, the service life of a sample is prolonged, and the problem of detecting weak pumping imaging signals submerged in system background noise is solved.

The invention discloses an impeller unbalance monitoring method based on a blade three-point identification visual technology. The impeller unbalance monitoring method comprises the steps that three identification points are marked on each blade; in the working process of the wind turbine generator, the cabin clearance monitoring camera is used for shooting images of the blades in real time; identifying the pixel coordinates of the identification points in the image through an image technology, and converting the pixel coordinates into world coordinates; fitting a blade track according to the world coordinates; and identifying the impeller imbalance condition according to the blade motion trail. According to the method, image data collected by a cabin clearance monitoring camera (located at the bottom of a cabin and close to a hub shooting blade) is utilized, pixel coordinates of marking points and internal and external parameters of the camera are recognized through an image technology, the positions of the marking points in a world coordinate system are converted, and the position of the marking points is determined according to the difference of tracks of the marking points of the three blades. And identifying the impeller imbalance condition of the wind generating set.

The invention provides an unsupervised multi-view three-dimensional reconstruction method based on a bidirectional attention mechanism, and mainly solves the problem of low three-dimensional reconstruction quality in a weak texture region and a complex shielding scene in the prior art. The scheme comprises the following steps: 1) inputting a multi-view image and camera parameters; 2) preliminarily extracting multi-scale features of an input image through a bidirectional feature pyramid network Bi-FPN, taking the multi-scale features as input data, performing enhancement through an attention mechanism, and then calculating a fusion feature map; 3) performing multi-stage depth estimation from coarse to fine by using the fused feature map; 4) calculating an initial depth map of a data enhancement branch; 5) fusing multi-source information to optimize the initial depth map, and generating a final refined depth map; and 6) converting the refined depth map into a point cloud model to obtain a reconstruction result. According to the method, the multi-scale features of the image can be extracted and fused more efficiently, so that the three-dimensional reconstruction quality of a weak texture region and a complex shielding scene is remarkably improved.

The invention relates to the field of heliostat calibration, and discloses a scheduling method for calibrating heliostats through cooperation of artificial light sources and cameras in a large-scale heliostat field, and the method comprises the following steps: determining the heliostat range covered by each camera, determining the heliostat range covered by each artificial light source, and determining the heliostat range covered by each camera; the method comprises the following steps: determining the center and size of a light spot in an image shot by a camera when the heliostats are calibrated, determining the heliostats which can be calibrated in the coverage range of each artificial light source-camera combination, regarding each effective calibration combination as a node to construct an undirected graph, dividing the nodes into a plurality of groups through a graph grouping algorithm, and ensuring that the nodes in the same group are not connected with each other, therefore, all combinations in the same group can execute calibration in parallel. According to the method disclosed by the invention, the problem of affiliation misjudgment caused by light spot interference between heliostats is solved, possible shadow and shielding problems are avoided, dynamic scheduling of the artificial light source and the camera is realized, and invalid operation time is shortened.

The invention discloses a rail transit intelligent inspection robot positioning system based on laser SLAM and inertial navigation, and relates to the field of real-time positioning, the rail transit intelligent inspection robot positioning system is characterized in that data are synchronously acquired through a laser radar, an IMU, a speedometer and an RGB-D camera, and high precision in rail positioning is realized; the point cloud filtering module extracts orbit feature points through an improved voxel grid algorithm, and the inertial navigation initialization module calculates an initial pose based on IMU data and establishes a motion constraint model; the map feature layering module divides the point cloud into a track surface, equipment and a background layer; and the data tight coupling module optimizes the pose, and the dynamic object elimination module eliminates obstacles, so that the SLAM optimization precision is ensured. And the global positioning compensation module performs repositioning through particle filtering to generate a 6DoF pose estimation semantic map. The method has the advantages that by fusing the laser SLAM and inertial navigation technologies, high-precision and stable rail transit inspection is realized, the positioning precision and the environmental adaptability are optimized, and the intelligent operation and maintenance efficiency is improved.

The present invention provides a parameter deviation determination method, apparatus and tool, a storage medium, and a computer device. The method comprises: determining that an adapter board is fixed to the tail end of a robot, wherein a calibration probe and a camera are fixed on the adapter board, and the robot is fixed on a base; controlling the robot to move, such that the calibration probe comes into contact with a calibration board, and obtaining a first relative position relationship between the calibration board and the base; controlling the tail end to move toward a calibration point, and when the tail end moves to the calibration point, controlling the camera to capture an image, wherein the image comprises the calibration board; on the basis of the image and the first relative position relationship, determining a second relative position relationship between the camera and the base during image capturing; and on the basis of the second relative position relationship and an ideal kinematics parameter of the robot, determining a kinematics parameter deviation of the robot. The present invention solves the technical problems that the robot kinematics parameter calibration process has high costs and low efficiency, and a calibration device is not portable.