180 results about "Camera auto-calibration" patented technology

This invention provides a system and method for runtime determination (self-diagnosis) of camera miscalibration (accuracy), typically related to camera extrinsics, based on historical statistics of runtime alignment scores for objects acquired in the scene, which are defined based on matching of observed and expected image data of trained object models. This arrangement avoids a need to cease runtime operation of the vision system and/or stop the production line that is served by the vision system to diagnose if the system's camera(s) remain calibrated. Under the assumption that objects or features inspected by the vision system over time are substantially the same, the vision system accumulates statistics of part alignment results and stores intermediate results to be used as indicator of current system accuracy. For multi-camera vision systems, cross validation is illustratively employed to identify individual problematic cameras. The system and method allows for faster, less-expensive and more-straightforward diagnosis of vision system failures related to deteriorating camera calibration.

Embodiments herein include systems, methods and articles of manufacture for calibrating a camera. In one embodiment, a computing system may be coupled to a calibration apparatus and the camera to programmatically identify the intrinsic properties of the camera. The calibration apparatus includes a plurality of light sources which are controlled by the computer system. By selectively activating one or more of the light sources, the computer system identifies correspondences that relate the 3D position of the light sources to the 2D image captured by the camera. The computer system then calculates the intrinsics of the camera using the 3D to 2D correspondences. After the intrinsics are measured, cameras may be further calibrated to in order to identify 3D locations of objects within their field of view in a presentation area. Using passive markers in a presentation area, computing system may use an iterative process that estimates the actual pose of the camera.

This invention provides a system and method to validate the accuracy of camera calibration in a single or multiple-camera embodiment, utilizing either 2D cameras or 3D imaging sensors. It relies upon an initial calibration process that generates and stores camera calibration parameters and residual statistics based upon images of a first calibration object. A subsequent validation process (a) acquires images of the first calibration object or a second calibration object having a known pattern and dimensions; (b) extracts features of the images of the first calibration object or the second calibration object; (c) predicts positions expected of features of the first calibration object or the second calibration object using the camera calibration parameters; and (d) computes a set of discrepancies between positions of the extracted features and the predicted positions of the features. The validation process then uses the computed set of discrepancies in a decision process that determines whether at least one of the discrepancies exceeds a predetermined threshold value. If so, recalibration is required. Where multiple cameras are employed, extrinsic parameters are determined and used in conjunction with the intrinsics.

A system and method for determining the adjustments that must be made to the individual images recorded by a multi-lens camera so that the images will fit together into a panorama. The camera is placed in the center of a structure, the edges of which have at least one row on indicia. Each camera records an image which includes the indicia along each edge that will be seamed with an edge of another image in order to form a panorama. Each edge of the structure which is along a seam that will be seamed with an edge of another image is recorded by two lenses on the camera. The amount of adjustment required to make the indicia in the two images fit together is then determined. The values of these adjustments are recorded along with an identification of the camera which recorded the images. Subsequent sets of images recorded by this same camera can then be seamed using the same adjustments.

The invention provides a robot tail end positioning deviation correction method and system. The present includes the following steps that: 101, a camera calibration system is set; 102, the relative positions of the tail end of a manipulator and the center of a camera are calibrated; 103, the camera photographs the images of all mark points in a calibration plate and analyzes the images so as to obtain a series of deviation quantity data under the condition that the tail end of the manipulator drives the camera to move and traverse different Z values; and 104, a space deviation distribution table is constructed; and 105, the deviation of the tail end of the robot can be obtained based on the space deviation distribution table. According to the method and system of the invention, the calibration coefficient of the camera is calibrated; the relative positions of the tail end of the manipulator and the center of the camera are calibrated; the camera photographs the images of all the mark points in the calibration plate and analyzes the images so as to obtain deviation quantity under the condition that the tail end of the manipulator drives the camera to move and traverse different Z values, and the deviation correction table is stored; and manipulator positioning is compensated through searching the deviation correction table, and the manipulator can move to a set position.

The present invention provides a three-dimensional chart, a parameter acquiring method and an information processing device that are used for carrying out camera calibration in a wide range with high precision. For this reason, a plurality of unit graphic forms the sizes of which are coded by using different cross-ratios are placed on side faces of a three-dimensional chart. The cross-ratios of unit graphic forms are calculated from a picked-up image of the three-dimensional chart, and by collating these with actual values, the position and orientation of the image-pickup point are determined. The shifting average of the heights of the unit graphic forms is made approximately proportional to the distance from the apex so that it is possible to reduce the limitation of image-pickup distances. A movable camera is attached to a subject-use camera, and upon picking up an image of the subject, an image of the three-dimensional chart is also picked up simultaneously. Based upon the position and orientation of the movable camera found out by the above-mentioned sequence of image-pickup processes and the relative position and orientation between the two cameras that have been preliminarily found, it is possible to determine the position and orientation of the subject-use camera.

An on-orbit geometric calibration method of an optical remote sensing camera aims at a domestic satellite platform and load design characteristics to build a strict imaging model, and uses an internal and external orientation element combination modeling method for geometric calibration treatment. The method is based on the strict imaging model for the geometric calibration treatment, and model parameters have clear physical meanings; 2) simultaneous decoupling of internal and external orientation elements can be realized by internal and external orientation element combination modeling; 3) the model can be used for a multiple linear array camera and multi-camera combination calibration, and has a strong universality; 4) according to the method, various factors causing image distortion in an imaging process can be fully considered, and high precision can be achieved.

A method for estimating the horizon in an image of a camera to provide camera auto-calibration in the pitch direction. The method includes taking an image of a scene and generating a texture map of the image using horizontal edge detection analysis to locate horizontal edges in the scene. The method also includes providing a motion map by providing image differencing between subsequent images to find areas in the scene with no motion while the vehicle is moving. The texture map and the motion map are combined to identify the areas in the image that do not move and contain horizontal edges. A horizontal projection is generated from the combined map by counting white dots in the map in the horizontal direction. The horizontal projection is smoothed to eliminate noise and the location of the horizon is estimated in the image by identifying the maximum peak in the horizontal projection.

A scope navigation apparatus, method and a program embodied computer readable medium for navigating a scope end that is to be inserted into an object. The scope end includes at least one sensor that senses a spatial location of the scope end. An image pickup device records one or more images of a calibration device, which includes a sensor that senses a location of the calibration device. A processor calibrates the images recorded by the image pickup device and corrects for intrinsic and extrinsic parameters using a calibration matrix.

The invention provides a three-dimensional reconstruction method for binocular stereo vision. The method comprises the steps of performing image pair collection: obtaining images of a calibration plate and an object; performing camera calibration: performing calibration on a camera based on a Zhengyou Zhang calibration method to obtain initial internal and external parameters of the camera; performing stereo rectification: performing rectification on a distortion parameter through epipolar constraint to obtain a rectified image pair; performing image processing: obtaining a region of interest,and balancing brightness difference between left and right images, thereby searching for matching points; performing stereo matching: implementing a multi-grid intensive stereo matching algorithm toobtain a continuous smooth disparity map; and performing point cloud rebuilding and model rebuilding: obtaining a point cloud chart of the object, performing point cloud optimization, and obtaining acomplete object model through triangulation of a greedy algorithm. The smooth model with no obvious difference with the real object can be obtained; and the method can be used for three-dimensional reconstruction of multiple scenes.

The invention discloses a vehicle queue length measurement method based on PTZ (Pan/Tilt/Zoom) camera fast calibration. The vehicle queue length measurement method based on the PTZ camera fast calibration comprises the following steps of choosing two vertically-crossed traffic markings to form a T-shaped scaling reference and establishing a conversion relation between coordinates of pixels in an image and coordinates of roadway corresponding points in a world coordinate system according to the defined models of the image coordinate system and the world coordinate system; acquiring video images of a traffic monitoring scene by adopting a PTZ camera, setting an ROI (Region Of Interests) of a lane, detecting the vehicle queue state in the ROI by the adoption of an adaptive background update algorithm and textural features, and acquiring the pixels and pixel coordinates of the tails of the vehicle queues; converting the detected pixel coordinates of the tails of the vehicle queues into the world coordinate and finally computing the length of the vehicle queues. The tail position of the vehicle queues is judged according to the textural features, and the measurement of length of the vehicle queues is finished by the combination of the camera, so that the vehicle queue length measurement method based on the PTZ camera fast calibration, disclosed by the invention, has the advantages of low cost, strong embedded type, and the like.

The invention discloses a directional calibration target for camera inner and outer parameter calibration. The directional calibration target is characterized by comprising a checkerboard and directional mark patterns, wherein the checkerboard is formed by black squares and white squares in alternate distribution; the directional mark patterns are arranged in a position near the center position of the checkerboard; the directional mark patterns are three mark circular rings or three mark circles; intersection points of any two diagonally connected black squares or intersection points of any two diagonally connected white squares are used as feature corner points of the directional calibration target; the feature corner points are used for camera calibration; and the directional mark patterns are used for judging the rotation direction of the directional calibration target. The directional calibration target has the advantages that in the camera calibration process, a computer can automatically judge the rotation direction of the directional calibration target; the intelligence and the flexibility of the camera calibration are improved; and the calibration complexity is reduced.

The present invention provides an apparatus and method for camera parameter calibration which is capable of easily and simply setting physical and optical characteristic parameters of a camera in order to acquire information on actual measurement of an image provided through the camera with high accuracy. The camera parameter calibration apparatus and method has an advantage of correct image analysis that it is capable of increasing accuracy of information of measurement through an image only with an intuitive interface manipulation, without taking a time-consuming and incorrect actual measurement procedure, by determining parameters of the space model corresponding to the image by displaying a 3D space model corresponding to a real space of the image on the image and changing and adjusting visual point parameters such that the 3D space model matches the display image, and regarding the determined parameters of the space model as camera parameters of the image.

The invention discloses an image processing method for a panoramic vehicle safety system based on multi-camera self calibration. The image processing method relates to automatic recognition, automatic correction, automatic view angle conversion and automatic splicing image conversion. The image processing method specially comprises the steps that calibration cloth recognition is conducted on collected images, and the position information of edge corner points on checkerboard calibration cloths of the collected images are extracted automatically; a distortion model is established, distortion parameters are iterated, and a distortion correction map is obtained; affine transformation is conducted on the distortion correction map to obtain images after view angle conversion; the images collected by a plurality of cameras are subjected to transformation processing and marked by encoded points, and the images collected by the cameras are spliced and integrated. Compared with the prior art, the image processing method for the panoramic vehicle safety system based on multi-camera self calibration has the following advantages that the method supports splicing of any multiple cameras, splicing is convenient and fast, a user only needs to input the number of the cameras, the calibration cloths are matched for use, and a panoramic image can be spliced in a full-automatic mode.

The invention discloses a multispectral light-field imaging method. The adopted hardware comprises a wideband filter array, an isomerism camera array, a control panel array and an information joint processing device, wherein the wideband filter array, the isomerism camera array, the control panel array and the information joint processing device are arranged in sequence in the light path direction. The imaging method comprises the steps of placing wideband filters with different wavelengths among each camera lens and sensor of the isomerism camera array so that each camera in the isomerism camera array can receive spectral information with a fixed waveband ; using the information joint processing device to conduct stereo matching based on a convolutional neural network on multipath information obtained by the camera array to obtain angular information of incident ray and obtain optical field information within a full field range; conducting camera calibration and view field aligning on distribution positions of cameras, and obtaining multi-waveband spectral information of which the number is three times the number of cameras under any camera perspective in the camera array through spectral demultiplexing. According to the multispectral light-field imaging method, multispectral optical field information of each pixel with the full field range can be obtained simultaneously, and thus dynamic and united obtaining of optical field and spectral information is achieved.

With an object of solving problems existing in the prior art, the invention provides a fully automatic calibration method for a high performance camera under a complicated background. The method is combined with a Robust's checkerboard corner detection method, and two groups of checkerboards corners are adopted to serve as filters on the basis of the characteristics of the corners to filter marker images. Eight filters of two types are reduced to four filters of two types, which means that the wave processing amount halves and therefore, the calibration speed increases. Further, the method utilizes a Zhang's camera calibration method to mark the camera calibration parameters. The method utilizes the marked camera calibration parameters to standardize images to be corrected, and a normalized correlation of the standardized images is calculated, and then sub-pixel precision checkerboard corners are obtained. The method then re-projects the coordinate of the checkerboard corners onto image space to obtain a precise coordinate of the corner image. The newly obtained coordinate of the corners is then substituted into the Zhang's calibration method to obtain new computed camera parameters. By repeating the above steps, a performer can obtain highly precise camera parameters. According to the embodiments of the invention, it is possible for a performer to complete automatic corner detection and camera calibration without having to resort to human-machine interactive operations.

A system for determining one or more camera calibration parameters is disclosed. The system comprises a processor and a memory. The processor is configured to: a) provide a first pattern for display on a display screen; b) receive a first image from a camera viewing the display screen; c) provide a second pattern for display on the display screen; and d) receive a second image from the camera viewing the display screen. The relative position of the display screen and the camera are the same as when the first image was captured using the camera. The processor is further configured to determine an image location which is a projection of a known physical location on the display screen by using at least in part a first feature identified in the first image and a second feature identified in the second image and determine one or more calibration parameters based at least in part on the determined image location. The memory is coupled to the processor and configured to provide the processor with instructions.

The invention relates to a system for measuring the height of a human body in a video image based on camera calibration and further discloses a method for measuring the height of a human body in a video image based on camera calibration. The system comprises a calibration point selecting module, a camera parameter calculating module, a body height measuring end point selecting module and a human body height calculating module. By the adoption of the system and the method, the height of a person erectly standing on the ground can be measured only by relying on monitored video image data after camera parameters and corresponding space transformation matrixes of the parameters are calculated. The height calculating process is simplified. The camera parameters are calculated according to the correspondence relation of image space coordinates and actual space coordinates of the same position point. The height of the person erectly standing on the ground is calculated by combining with the camera parameters and foot bottom point and head top point measurement end point information and utilizing a height calculating algorithm.