1183 results about "Rotation matrix" patented technology

A system for navigating a medical device through the lumens and cavities in an operating region in a subject, comprising an imaging system for displaying an image of the operating region, including a representation of the distal end of the medical device in the operating region. The system also includes a localization system for determining the position of the medical device in a frame of reference translatable to the displayed image. Finally, the system includes an algorithm for evaluating one or more rotation matrix using a cost function to determine an optimum rotation matrix for performing transformation of a vector in the local frame of the localization system to that of the reference frame of the navigation system. The rotation matrix can then provide a scale invariant transformation or “registration” of the coordinate systems of the localization system and the navigation system. This allows navigation to be performed to a significant extent from the localization system display alone, which avoids the frequent x-ray irradiation that occurs during the use of fluoro imaging for navigation purposes.

Methods and apparatuses for transposing a matrix using a vector look up unit. In one aspect of the invention, a method for matrix transposition includes: rotating in a vector register a first row of a matrix to generate a first row, of elements; writing simultaneously into a plurality of look up units the first row of elements indexed by a first row of indices in a vector register; looking up simultaneously from the plurality of look up units a second row of elements indexed by a second row of indices in a vector register; and rotating in a vector register the second row of elements to generate a third row of elements.

The invention provides a joint measurement method based on a laser radar and a binocular visible light camera to obtain accurate and dense three-dimensional information simply and efficiently. The joint measurement method comprises assuming that the laser radar is a camera device with a fixed internal reference; directly projecting three-dimensional point cloud data into a two-dimensional image, calculating rotation and translation relationships between the laser radar device and the binocular camera by using an image processing method and the matching between the two-dimensional images; creatively introducing an idea for obtaining a matrix norm and a matrix trace to solve a rotation matrix; finally fusing laser radar and binocular stereo vision point cloud data. The method not only can obtain an accurate position and attitude information, but also can reconstruct the special texture and feature information of a target surface, which has a high application value for spacecraft dockingand hostile satellite capture in the military field and workpiece measurement and unmanned driving in the civilian field.

Aspects of a method and system for utilizing Givens rotation expressions for quantization for a general beamforming matrix in feedback information. In one aspect of the invention, feedback information is computed at the receiving MIMO wireless device based on a geometric mean decomposition (GMD) method. The feedback information may include a matrix that describes a wireless medium. The matrix may represent a multiplicative product of at least one rotation matrix and at least one diagonal phase rotation matrix. Each of the rotation matrices may include at least one matrix element whose value is based on Givens rotation angle. The transmitting MIMO wireless device may subsequently transmit a plurality of signals via the wireless medium based on the received matrix information. The signal strength and/or signal to noise ratio (SNR) measurement (as measured in decibels, for example) associated with each of the transmitted plurality of signals may be about equal.

An apparatus and method to enhance dead-reckoning navigation using inertial sensor measurements based on images from a camera are disclosed. A camera build into a mobile device is used to calibrate inertial sensors and rotation matrices. Images from a camera may be used (1) to remove a gravitational element from accelerometer measurements; (2) to set a scaling factor and an offset for a gyrometer; and (3) to set initial and updated values for rotation matrices.

Aspects of a method and system for utilizing Givens rotation expressions for asymmetric beamforming matrices in explicit feedback information are presented. In one aspect of the invention, Givens matrices may be utilized to reduce a quantity of information communicated in explicit feedback information via an uplink RF channel. The explicit feedback information may include specifications for a feedback beamforming matrix that may be utilized when transmitting signals via a corresponding downlink RF channel. The feedback beamforming matrix may represent a rotated version of an un-rotated matrix. The Givens matrices may be utilized to apply one or more Givens rotations to un-rotated matrix. The feedback beamforming matrix may be computed based on a matrix product of a plurality of Givens matrices. The feedback beamforming matrix may be encoded utilizing fewer bits than may be required to encode the un-rotated matrix.

A three-dimensional rebuilding method based on laser and camera data fusion is characterized in that the rebuilding method comprises the following steps: (1) a C++ language is adopted to compile a laser data automatic collecting platform based on a radar principle; (2) a rotation matrix R and a translation vector T are arranged between a camera coordinate system and a laser coordinate system; (3) a motion object is extracted and subdivided by utilizing an optical flow field region merging algorithm, thus further subdividing the point cloud corresponding to the motion object; and (4) guarantee of point cloud and image texture on the precise positioning is provided for the three-dimensional image texture mapping, thus realizing the three-dimensional rebuilding system based on data fusion. The three-dimensional rebuilding method has the advantages of quickly and automatically collecting and processing laser data, quickly completing the external labeling of the laser and CCD, effectively extracting and subdividing effective point clouds of the object in complex environment and exactly completing the three-dimensional rebuilding of the laser and CCD data of the object.

A signal processing method in an MIMO multi-carrier system is disclosed comprising: receiving by a receiver signals of a plurality of sub-carriers transmitted from a transmitter; dividing the sub-carriers into a plurality of sub-carrier blocks according to the correlation between adjacent sub-carriers, each sub-carrier block containing K sub-carriers; selecting a feedback sub-carrier pre-coding matrix ( ) and a rotation matrix ( ) for each sub-carrier block, and then sending the information on the pre-coding matrix and the rotation matrix back to the transmitting end. The present invention provides the method and device for effectively settling the feedback problem in an MIMO/OFDMA system, thereby greatly reducing the number of pre-coding weight matrices needed to feed back to the transmitting device.

The invention provides a multi-camera system calibrating method based on an optical imaging test head and a visual graph structure. The method comprises the following steps: independently calibrating each camera by the optical imaging test head to obtain the initial values of the internal parameter and aberration parameter of each camera; calibrating the multiple cameras two by two, and obtaining the fundamental matrix, polar constraint, rotation matrix and translation vector between every two cameras with a plurality of overlapped regions at a view field by means of linear estimation; building the connection relationship among the multiple cameras according to the graph theory and the visual graph structure, and estimating the rotation vector quantity initial value and translation vector quantity initial value of each camera relative to the referred cameras by a shortest path method; and optimally estimating all the internal parameters and external parameters of the all cameras and the acquired three-dimensional sign point set of the optical imaging test head by a sparse bundling and adjusting algorithm to obtain a high-precision calibrating result. The multi-camera system calibrating method is simple in a calibrating process from the partial situation to the overall situation and from the robust to the precise, ensures high-precise and robust calibration, and is applied to calibrating multi-camera systems with different measurement ranges and different distribution structures.

The invention discloses a method for calibrating external parameters based on a camera and a three-dimensional laser radar, which comprises the following steps: according to a covariance of measurement errors in the perpendicular line direction from a three-dimensional laser radar coordinate system origin to different position target planes and a covariance of measurement errors in a conversion relationship from a three-dimensional laser radar coordinate system to a camera coordinate system in the perpendicular line direction, acquiring an equation of a quadratic sum of the variance including the variance of the camera measurement noise and the variance of the three-dimensional laser radar measurement noise in the covariance of the measurement errors in the conversion relationship; and calibrating a rotation matrix with maximum likelihood estimate by using the reciprocal of the quadratic sum of the variances of all obtained measurement noise as a weighting coefficient. The invention also discloses a system for calibrating the external parameters based on the camera and the three-dimensional laser radar at the same time. The effect of the measurement errors on the rotation matrix to be calibrated is taken into consideration during calibrating, and the algorithm of the maximum likelihood estimate is adopted for the measurement errors in the calibrated result of the rotation matrix, so the calibrating result is more accurate.

The invention discloses a virtual reality realization method based on the augmented reality. The method includes: 1) acquiring a depth image sequence and a RGB sequence of a scene through a camera; 2) generating a RGBD four-channel image sequence of the scene according to the acquired depth image sequence and the RGB sequence; 3) calculating a rotation matrix and a translation vector of the camera between two frames according to the RGBD, recognizing a target object and a planar structure in the scene and position information thereof in the three-dimensional space from the RGBD of the scene, and converting the RGBD to a binocular view sequence; and 4) presenting the binocular view sequence on a screen of the camera, drawing a virtual three-dimensional model of the target object in the scene according to the position information of the planar structure in the three-dimensional space in the scene, transforming the virtual three-dimensional model according to the rotation matrix and the translation vector of the camera, and enabling the virtual three-dimensional model and the attached planar structure to be relatively static. According to the method, the image to be presented can be accurately and rapidly calculated.

The application of the invention discloses a combined calibration method for multiple sensors of a mobile robot. The mobile robot comprises a 2D laser radar and a camera. The method comprises the following steps of: S1, performing internal parameter calibration on the camera by use of a pinhole cameramodel, so as to obtain an internal parameter matrix, which is as shown in the description, of the camera; S2, placing the camera and the 2D laser radar on fixed positions of the mobile robot, and keeping the 2D laser radar and the camera constant in a movement process of the mobile robot; S3, acquiring the position of the camera in a world coordinate system at a moment ti, wherein the position of the camera is as shown in the description, and I is a positive integer; S4, acquiring the position of the 2D laser radar in a world coordinate system at the moment ti, wherein the position of the 2D laser radar is as shown in the description; S5, repeating the S3 and S4 until i is not less than 4; and S6, obtaining a rotation matrix Rcl and a translation matrix tcl of the camera and the 2D laser radar according to an equation as shown in the description. The technical scheme of the application of the invention completely breaks away from the restriction of a calibration target, calibration can be performed under various environments, real-time calibration can be performed in a use process, the problem that positioning error is caused since parameters of existing mobile robots are calibrated only before leaving factory and the parameters fluctuate in the later stage, and users can perform calibration conveniently in the use process.

A method for self-recalibration of a structured light vision system including a camera and a projector. A camera plane and a projector plane are defined, a Homography matrix between the camera plane and the projector plane is computed, and a translation vector and a rotation matrix are determined from Homography-based constraints. A computer vision system implementing the method is also described.

The invention provides an indoor three-dimensional scene reconstruction method employing plane features, and the method comprises the steps: obtaining an RGB image and a depth image of an indoor scene in real time, and completing the reconstruction of a single-frame three-dimensional point cloud; carrying out the feature extraction of two adjacent RGB images, and obtaining the initial rotating matrixes of the two adjacent three-dimensional point clouds; carrying out the downsampling of each three-dimensional point cloud, and extracting the plane features of the indoor scene from each three-dimensional point cloud; determining each plane position; calculating an error rotating matrix; correcting the initial rotating matrixes, and carrying out the jointing and registering of each two three-dimensional point clouds; and finally achieving the reconstruction of the indoor three-dimensional scene through the jointing and registering of each three-dimensional point cloud. The method carries out the error elimination through employing the geometric features of the point clouds, and extracts the plane features of the point clouds quickly and effectively. The success rate of the matching of the plane features of the current and former point clouds is higher. According to the plane features, the method judges the type of the planes, calculates the error matrix, corrects the initial rotating matrix, and obtains a more accurate indoor three-dimensional point cloud map.

The embodiment of the invention provides a mechanical arm tail end camera hand-eye calibration method and system, and the method comprises the steps: obtaining a calibration image collected by a calibration area when a mechanical arm performs translation and rotation for multiple times at the same time; Obtaining a hand-eye calibration matrix based on the mechanical arm pose information and the calibration image external parameter information; And calibrating the hand-eye relationship of the tail end of the mechanical arm by using the hand-eye calibration matrix. According to the scheme, the calibration of the camera is completed by utilizing spatial motion and image acquisition at a plurality of different positions; According to the principle that the hand-eye relationship is constrainedby multiple spatial relative positions, only the positions of at least three spatial positions relative to the base and external parameters of the camera need to be obtained in the calibration process, and the calibration process can be universal for different mechanical arm models, the number of freedom degrees and camera models; According to the scheme, translation and rotation matrix transformation is utilized, the mechanical arm tail end coordinates are projected to the pixel coordinates, and calibration of the hand-eye relation between the camera and the mechanical arm tail end when the mechanical arm tail end has rotation and translation movement at the same time is obtained.

A method and system for calibrating a wireless sensor device are disclosed. In a first aspect, the method comprises determining a vertical calibration vector and determining a rotation matrix using the vertical calibration vector to line up native axes of the wireless sensor device with body axes. In a second aspect, a wireless sensor device comprises a processor and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to determine a vertical calibration vector and to determine a rotation matrix using the vertical calibration vector to line up native axes of the wireless sensor device with body axes.

The present invention provides an antenna-array-based multiple-input multiple-output orthogonal-frequency-division-multiplexing (MIMO-OFDM) system and a pre-coding and feedback method used in the same. The present invention uses QR decompositions of the MIMO channel matrixes to parameterize the channel state information (CSI) of every OFDM frequency band. In addition, the present invention feeds back the information related to θ and φ in the Givens rotation matrixes of the partial frequency bands and then uses an interpolation method to generate θ and φ in the Givens rotation matrixes of all the frequency bands, which further is able to represent the CSI of all the frequency bands. In this way, the present invention has advantages of low complexity and low feedback rate requirement.

The invention discloses a method and a device for measuring surface topographies of mirror and mirror-like objects. Phase measurement deflectometry is adopted to measure mirror and mirror-like surface shapes, a combination between a liquid crystal display and a planar mirror serves as a calibration plate, the liquid crystal display is fixed and can not move, the planar mirror moves freely for four times, an image reflected by the planar mirror is photographed by a CCD detector, linear solution and beam method adjustment are then used for completing calibration on inner parameters of the camera, global pose estimation is used for completing calibration on the relative relation between the liquid crystal display and the camera, and finally, a three-dimensional topography of a to-be-detected mirror surface is calculated and obtained through a gradient integral of the phase measurement deflectometry. According to the device and the method of the invention, defects that the calibration plate is needed and a precise positioning control point is attached to the planer mirror during the calibration process in the traditional method are overcome, the measurement cost is low, and he measurement speed is quick; and constraint conditions such as rotation matrix orthogonality during a perspective imaging process and a fourier transform method are introduced for corresponding point matching, and influences by high noise and multiframe processing on three-dimensional topography recovery can be overcome.

The invention provides a calibration method of a camera and inertial sensor integrated positioning and attitude determining system. The method comprises the following steps: calibrating the intrinsic matrix of the camera; shooting a plurality of images of a calibration object with known dimensions from different angles, and recording the roll angle and the pitch angle output by the inertial sensor when each image is shot; defining a world coordinate system, a camera coordinate system, an inertial sensor coordinate system and a geomagnetic coordinate system; calculating the rotation matrix from the world coordinate system to the camera coordinate system at the moment based on the image information and spatial information of the calibration object in each image; integrating the shot images pairwise, establishing an equation set with respect to the rotation matrix from the inertial sensor coordinate system to the camera coordinate system for each group, and solving the equation set to calculate the rotation matrix from the inertial sensor coordinate system to the camera coordinate system; and establishing an equation set with respect to the rotation matrix from the geomagnetic coordinate system to the world coordinate system for each image, and solving the equation set to calculate the rotation matrix from the geomagnetic coordinate system to the world coordinate system.

A rotation matrix and a translation vector between a basic camera (12) and a reference camera (14) are read out from a parameter storage section (26). At a projection conversion matrix calculating section (28), a projection conversion matrix capable of overlapping the road plane area included in images picked up by the basic camera (12) and the reference camera (14) is calculated by using the rotation matrix and the translation vector.

The present invention discloses a camera positioning correction calibration method and a system for realizing the method, belonging to the technical field of image virtual production. Through the intrinsic relationship among a lens parameter, an imaging surface and an optical tracking device, by using the world coordinate and image point coordinate of N mark points on a background screen and the internal parameter and lens distortion parameter of a camera lens, the rotation matrix between a camera coordinate system and a world coordinate system and the translation vector of a camera perspective center in the world coordinate system are obtained, combined with the current position information given by a camera posture external tracking device in a current state, camera correction calibration information and viewing angle are obtained, the lookup table with a focusing distance and a focus length relationship is established, thus when a camera position, a lens focal distance and a focusing distance change, the position of the virtual camera of the virtual production system is fully automatically positioned and corrected, and thus a real video frame picture and a virtual frame image generated by a computer can be matched perfectly.

A method for measuring space-circle geometric parameter based on binocular stereo-vision includes confirming parameter and one-order radial distortion parameter separately in left-right video cameras, calculating out rotary matrix and translation vector presenting relative position relation of left-right video cameras, utilizing left-right video cameras to obtain two frame of images containing space-circle oval image and carrying out distortion calibration on two obtained images and directly calculating out all geometric parameters of space-circle in linear way by adapting oval image of distortion-calibrated image plane.

The invention discloses a method for establishing a relation between a scene stereoscopic depth and a vision difference in a binocular stereoscopic vision system. the method comprises the steps of firstly, solving inner parameters, and relative rotary matrixes and translation vectors of left and right cameras; then, analyzing a main error source and an error model of the binocular stereoscopic vision system; then, analyzing influences of the main error on a base line length and the vision difference of the parallel binocular stereoscopic vision system; then, establishing a common relation model of the scene stereoscopic depth and the vision difference in the binocular stereoscopic vision system; obtaining depth information by a laser distance measuring instrument by selecting a certain amount of demarcation points and carrying out demarcation based on a least square method to solve a relation model between the scene stereoscopic depth and the vision difference in the binocular stereoscopic vision system; and finally, solving the vision difference in left and right images through a corresponding fixed matching method so as to realize accurate recovery and three-dimensional reestablishment of the scene stereoscopic depth. The method has the beneficial effect of directly, simply, accurately and extremely improving the accuracy of the stereoscopic depth recovery and the three-dimensional reestablishment.