15 results about "Binocular disparity" patented technology

The invention discloses a vehicle-mounted HUD optical performance comprehensive detection method, and aims to solve the problems that a traditional detection method depends on manual operation and is low in detection efficiency and large in error. Project loading and test starting, picture height position calibration, multi-parameter test, brightness and chromaticity test, ghosting test, static distortion test and binocular parallax test items are automatically implemented through detection equipment, and accurate control (such as application of camera pixel-millimeter ratio) of advanced image recognition algorithm and equipment in the test process is carried out. The vehicle machine controls the step number of the curved mirror motor, and the industrial personal computer controls the motion module, so that high-precision measurement of optical parameters is realized, and the test efficiency and the test accuracy are improved.

A method for calibrating a binocular camera calibration parameter, an apparatus, a computer device, and a medium. The method comprises: acquiring a binocular disparity map and / or a binocular depth map; performing epipolar alignment detection on the binocular disparity map and / or the binocular depth map to obtain an epipolar alignment error; and on the basis of the epipolar alignment error and a first preset threshold, determining a target calibration parameter to be calibrated of a binocular camera. In the solution, in the process of calibrating the binocular camera calibration parameter, the epipolar alignment error is obtained by performing epipolar alignment detection on the binocular disparity map and / or the binocular depth map, and the target calibration parameter of the binocular camera is determined on the basis of the epipolar alignment error, thereby not only simplifying the calculation of the epipolar alignment error but also improving the precision of the epipolar alignment error, thus enhancing the accuracy of calibration of the calibration parameter.

The invention discloses an anti-jitter data acquisition and obstacle recognition method for a rail transit vehicle, and relates to the technical field of rail transit vehicle data acquisition and processing, continuous four frames of original images are acquired through a binocular camera by adopting synchronous and staggered shooting, and global motion estimation is performed in combination with acquired sensor data; local pixel level alignment is realized by using a preset image layer and pixel grid division, a stable image is generated through weighted fusion, local features of the image are optimized based on a multi-head attention mechanism, the stable image is mapped to a high-dimensional vector space by using a depth encoder, motion correction information is fused, and finally, the motion correction information is obtained. A deep reconstruction network is combined with binocular parallax to generate a three-dimensional point cloud, three-dimensional coordinate changes are monitored in real time, obstacle recognition and early warning are achieved, high-quality images can be obtained in the violent vibration environment of a vehicle, the data acquisition precision and the real-time performance and accuracy of obstacle detection are improved, and the operation safety of rail traffic is effectively guaranteed.

The invention discloses an integrated three-dimensional space modeling method based on Gaussian splashing and a three-dimensional point cloud. The method comprises the following steps: step 1, converting a scene multi-view image and depth data into the three-dimensional point cloud; 2, constructing a point sequence input set; step 3, inputting the point sequence input set into a PointMamba model; 4, performing Gaussian parameter initialization, performing scale expansion on a local sparse region, and performing direction constraint on a global key region; 5, obtaining a prediction depth map through a binocular parallax matching algorithm, calculating a rendering depth map of the initial Gaussian point set, and adjusting the optimization intensity; and step 6, executing an adaptive encryption operation, and outputting a three-dimensional space model. According to the method, high-precision three-dimensional reconstruction of a complex scene is realized, and the method is suitable for scenes needing high-density point cloud modeling and semantic understanding, such as building scanning, industrial detection and virtual reality.

The invention discloses a quantitative evaluation method, system and device of a stereoscopic visual function and a storage medium, and belongs to the technical field of visual function detection and evaluation, the method comprises the steps that interactive response of a user to a visual stimulation image is continuously acquired, and the image comprises a target stimulation object and at least one interference stimulation object; according to the response result, adopting an adaptive algorithm to iteratively update the binocular parallax parameter until the change trend meets a preset convergence condition, and outputting a first binocular parallax parameter; and calculating and outputting a stereoscopic vision sharpness threshold value according to the parameters, so that by implementing the method and the device, real binocular parallax perception and cognitive judgment based on monocular clues can be effectively distinguished, the stereoscopic vision sharpness can be accurately determined, and the accuracy, objectivity and reliability of stereoscopic vision detection are improved.

An extended reality image device according to the embodiment of the present invention includes: an optical system forming plurality of focal planes; a sensor obtaining user gaze information; a processor selecting one of the plurality of focal planes based on the gaze information, changing the focus of the optical system to form focus on the selected focal plane, and generating a binocular disparity focal image; and a display outputting the binocular disparity focal image under the control of the processor, wherein a comfortable viewing zone for the user exists within plurality of depth of fields by the plurality of focal planes formed.

A novel knowledge distillation method for binocular disparity to monocular depth is disclosed. S1: Training the disparity-depth conversion module: First training data is input into a pre-trained binocular stereo disparity teacher model to obtain a disparity map; the first training data includes left-eye and right-eye color images; the disparity map and the original disparity reference map are input into the disparity-depth conversion module to obtain a pseudo-labeled depth map; a loss function is calculated based on the pseudo-labeled depth map, and the parameters of the disparity-depth conversion module are updated; S2: The pseudo-labeled depth map output by the disparity-depth conversion module and the original true-labeled depth map are mixed to obtain a mixed-labeled depth map; S3: Training the monocular depth estimation student model: The monocular depth estimation student model is trained using second training data; the second training data includes the mixed-labeled depth map and the corresponding original reference map. This invention enables training on datasets with relatively low data volume and improves global accuracy.

The application relates to a basketball tracking and main ball marking method, device and storage medium, wherein the method comprises the following steps: camera calibration; obtaining a basketball video frame; establishing a single-camera tracking queue; establishing single-camera basketball tracking; calculating the average value of the distance information change of a basketball object in a time window for the continuously tracked basketball object; judging whether the average value exceeds a threshold value; if yes, marking as a motion state; determining the projection error sum of all basketball objects marked as the motion state in different camera perspectives, and obtaining an error matrix; processing the error matrix based on the maximum bipartite matching principle to obtain a multi-camera basketball matching result; if the matching is successful, performing depth estimation on the image coordinates of the basketball based on a binocular disparity method; converting the depth estimation result into a real coordinate system to obtain three-dimensional coordinates; judging whether the basketball is in a target field; and if yes, marking as a main ball. Compared with the prior art, the application has the advantages of stable detection, high detection precision and the like.

The invention discloses a binocular camera calibration parameter calibration method and device, computer equipment and a medium. The method comprises the steps of obtaining a binocular disparity map and / or a binocular depth map; performing epipolar alignment detection on the binocular parallax image and / or the binocular depth image to obtain an epipolar alignment error; and determining a target calibration parameter of the binocular camera to be calibrated based on the epipolar alignment error and a first preset threshold. In the calibration process of the calibration parameters of the binocular camera, epipolar alignment detection is carried out on the binocular disparity map and / or the binocular depth map to obtain the epipolar alignment error, and the target calibration parameters of the binocular camera are determined based on the epipolar alignment error, so that the calculation of the epipolar alignment error is simplified, the precision of the epipolar alignment error is improved, and the calibration accuracy of the binocular camera is improved. And the calibration accuracy of the calibration parameters is improved.

A method, system and / or spectacle eyewear device for modifying the color vision of a person while viewing a color image emitted in linearly polarized light by a display device includes a first lens and a second lens, wherein the lenses each include a color-selective partial polarization filter and the polarization axes the filters are orientated non-parallel to each other and are configured so that a person experiences binocular rivalry due to spectral binocular disparity with respect to the polarized light emitted by the display device. In some variations the polarization axes of the filters are oriented in such a way that the intensity of binocular rivalry is maintained for rotations of the polarized light and / or display device by 45 degrees and by 90 degrees. In some variations the lenses appear substantially identical when viewed in non-polarized light. In some variations the person has color blindness or color vision deficiency.

The application provides an image processing method, device and equipment, the method comprising: obtaining a first original image and a second original image corresponding to a target object; obtaining a first disparity image by using a deep learning algorithm based on the first original image and the second original image; obtaining a second disparity image by using a target binocular algorithm based on the first original image and the second original image; fusing the first disparity image and the second disparity image to obtain a target disparity image; and generating a depth image corresponding to the target object based on the target disparity image. Through the technical scheme of the application, the disparity image of the deep learning algorithm and the disparity image of the target binocular algorithm are fused to obtain a high-precision noise-free target disparity image for distance measurement, and the advantages of the deep learning algorithm and the target binocular algorithm in binocular disparity estimation are fully utilized.

The invention provides a monocular model and binocular model fused parallax correction method and device, a medium, a program product and a terminal, and the method comprises the steps: obtaining a first monocular image and a second monocular image, carrying out the feature map extraction operation, and generating a corresponding first feature map and a corresponding second feature map; executing model distillation operation through the initial monocular model to obtain a distillation monocular model; inputting the first feature map to a distillation monocular model, and generating a relative parallax label; inputting the first feature map and the second feature map into a binocular parallax estimation model at the same time to generate a preliminary parallax map; and finally, generating a corrected real disparity map by fusing the initial disparity map and the relative disparity label. The inherent problem of scale blurring of a monocular model is solved, and the parallax estimation precision is improved by assisting a binocular model through a distillation monocular model. Through model distillation and multi-modal feature fusion, the defects of insufficient annotation data and scale uncertainty are overcome.

The invention relates to a vehicle-mounted suspension display device. The in-vehicle floating display device according to one embodiment of the present invention comprises: an image generation device for outputting a projection image; and a mirror that reflects the projection image from the image generation device and outputs a floating image based on the inverted real image. The reflecting mirror comprises a deformation reflecting mirror or a deformation Fresnel concave reflecting mirror. As a result, it is possible to realize a large-screen clear floating image, and to reduce the feeling of fatigue caused by parallax of both eyes.

The invention provides an automatic parallax adjusting system and an automatic parallax adjusting method. The automatic parallax adjusting system comprises a pair of cameras and a controller. The pair of cameras is used for shooting an object to obtain a first image and a second image. The pair of cameras comprises two lenses, and a distance exists between the two lenses. A controller is electrically coupled to the pair of cameras and configured to perform: correcting a first image with a first correction matrix and correcting a second image with a second correction matrix; cutting the first correction image and the second correction image; defining a comfortable range of a binocular focusing distance according to a viewing distance from the stereoscopic display to the eyes of the user; and calculating a corrected binocular parallax according to the comfort range, the first cut image and the second cut image.

The application provides a kind of image rectification method based on binocular disparity, comprising: obtaining the first view image and the second view image of different depth of field of target scene;The first view image and the second view image are adjusted to the same preset size;Determine the relative position attitude of the first view image and the second view image;According to the relative position attitude, the corresponding pixel points in the first view image and the second view image are adjusted to be aligned in horizontal direction;The first view image and the second view image are binocular depth estimation to obtain the first image, and the first view image or the second view image with relatively smaller depth of field is monocular depth estimation to obtain the second image;The first image and the second image are image fusion.The rectification method provided by the application can successfully generate long-range and near view disparity map, and is obviously superior to monocular disparity estimation method in accuracy.