975 results about "Parallax" patented technology

The invention relates to the technical field of three-dimensional model adjustment, in particular to a three-dimensional model adjustment method and system and a medium. The method comprises the following steps: obtaining a multi-angle image of an original model, carrying out multi-view normalization on the multi-angle image, generating a normalized view image set, extracting feature points of the original model, carrying out parallax correction on the feature points, reconstructing a simulation three-dimensional model, collecting basic purpose data of the model, carrying out ideal demand mapping through the data, and carrying out ideal demand mapping. The method comprises the following steps: determining an ideal three-dimensional model structure, carrying out core region segmentation on a reconstruction model according to basic purpose data to obtain key region model slices, carrying out highlight region comparison with the ideal model structure, analyzing model differences, determining a structure adjustment amplitude interval according to a comparison result, and carrying out cyclic fine adjustment correction on the key region model slices to obtain a three-dimensional model. And the three-dimensional model is consistent with the ideal three-dimensional model in structure, so that the optimized three-dimensional model is generated. According to the invention, efficient and accurate three-dimensional model adjustment and optimization are realized.

The invention discloses an automobile leather defect detection method and system based on visual inspection, and relates to the technical field of industrial visual inspection, and the method comprises the steps: reconstructing the three-dimensional shape of a leather surface and generating a three-dimensional point cloud picture by analyzing the parallax relation and illumination direction reflection characteristics among multi-view automobile leather images; automobile leather surface curvature change characteristics of the three-dimensional point cloud picture are extracted, multi-scale texture analysis is carried out, and potential defect areas are identified and marked; through a three-dimensional shape measurement method, defect three-dimensional shape characteristics of the potential defect area are extracted, and defect three-dimensional geometric parameters are calculated; by analyzing defect geometrical characteristics and spatial distribution rules of the defect three-dimensional geometrical parameters and utilizing a preset grading judgment rule to divide defect grades, an automobile leather quality evaluation report containing defect three-dimensional coordinates is generated; according to the method, through combination of curvature-texture multi-scale fusion detection, the recognition capability of complex surface defects is remarkably enhanced.

The invention discloses a cradle head tracking method and device based on a binocular camera and a storage medium, and relates to the technical field of computer vision, and the method comprises the steps: processing image data based on a binocular parallax principle, and generating a three-dimensional coordinate of a center point of a tracking target; based on the three-dimensional coordinates of the camera coordinate system and the offset from the optical center of the camera to the rotation center of the holder, generating three-dimensional holder coordinates through coordinate transformation solution; determining a historical track based on the tracking target feature information and a historical target feature matching result, and outputting an identifier and a three-dimensional position observation value through correlation verification of a three-dimensional holder coordinate and the historical track; inputting an observation updating equation correction state through the identifier and the three-dimensional position observation value, and outputting a three-dimensional prediction position; based on the three-dimensional prediction position and a deviation formula, calculating the angle deviation with the camera image center under the holder coordinate system, and driving the holder to center the target in the picture center according to the angle deviation. The problem that the target tracking effect is poor is solved, and the robustness of target tracking in a complex scene is improved.

The invention discloses a shock wave overpressure field global measurement method based on multi-view image fusion, belongs to the technical field of explosive shock wave measurement, and is suitable for weapon equipment power evaluation and blasting safety analysis. The method comprises the following steps of: synchronously acquiring a time sequence image of the whole explosion process through a distributed multi-view high-speed imaging system, preprocessing the image by adopting pixel-by-pixel comparison, square operation enhancement and normalization processing, and positioning a shock wave edge contour; the blasting center coordinate is positioned through binocular parallax, the shock wave initial radius is determined by combining spatial domain analysis, and the key feature points of the front and rear edges of the wavefront are detected by using a dynamic search window and a radial gradient field. Based on multi-view constraints, a three-dimensional point cloud is generated through direct linear triangulation, and a three-dimensional wave front form is reconstructed in combination with least square spherical fitting. And finally, constructing a wavefront radius-time evolution model, and deducing a quantitative relationship between the instantaneous propagation velocity and the peak overpressure in combination with a Ranki ne-Huton iot relationship, thereby realizing the global high-precision calculation of the overpressure field.

The invention discloses a robot obstacle avoidance method and system based on millimeter wave radar sparse point cloud, and relates to the technical field of obstacle avoidance recognition. A robot obstacle avoidance system based on millimeter wave radar sparse point cloud comprises a point cloud acquisition module, a negative obstacle identification module, a weak obstacle identification module, a point cluster identification module, a risk map module, a tentative verification module and an obstacle avoidance decision module. According to the invention, suspected obstacle point clusters are extracted based on a reflection intensity threshold and a spatial proximity relation in an enhanced point cloud, a theoretical parallax model of a real static obstacle is constructed under the constraint of a robot motion trajectory, and Doppler velocity distribution of each frame is combined with a static obstacle Doppler physical law for comparison. And classifying the point clusters which do not meet the multi-view geometric consistency or Doppler physical law, and distinguishing multipath false point clusters from dynamic point clusters.

The invention relates to the technical field of three-dimensional imaging, in particular to a four-eye structured light stereoscopic vision imaging method, which comprises the following steps of: arranging four cameras and synchronously acquiring multi-view image data with structured light stripes; carrying out image preprocessing and stripe code identification on the obtained four-view-angle structured light image data, and extracting structured light stripe center line positions and corresponding space projection information under each view angle; generating three-dimensional point cloud data of the high-precision target sample by using parallax calculation and a three-dimensional reconstruction algorithm, and completing spatial registration and filtering optimization of point cloud; fusing the point cloud and the light intensity data by combining the reflection intensity information of the multi-view structured light stripes to generate a composite data set containing space and spectral information; and constructing a dense parallax field and executing three-dimensional consistency verification, and generating a high-fidelity three-dimensional reconstruction model with a complete topological relation and sparse shielding compensation capability. According to the invention, the problems of insufficient view angle coverage, shielding area information loss, difficult edge structure matching and the like of traditional stereoscopic vision imaging can be solved.

The invention discloses a naked-eye 3D display optimization method based on real-time eyeball tracking, and particularly relates to the technical field of naked-eye 3D display, and the method comprises the steps: capturing eyeball movement data in real time through a visual angle tracking sensor, and collecting illumination information in combination with an ambient light sensor; depth perception parameters are calculated based on pupil diameter variation and frequency, and a time sequence prediction type dynamic compensation coefficient is generated in combination with eyeball movement acceleration; acquiring an initial fixation point coordinate by using an improved spherical projection mapping model, and performing compensation coefficient correction to obtain a real-time coordinate; and finally, according to the real-time coordinates, dynamically adjusting the refractive index distribution of the nanostructure layer, the rotation angle of the polarizer, the focal length of the optical lens and other optical modulation parameters. The real-time distance is calculated through the binocular parallax algorithm, the depth mapping value is generated by combining the focal length of the camera and the baseline distance, the method can adapt to the illumination change and the user view angle, and the 3D display effect is optimized.

The invention relates to the technical field of goods shelf detection, in particular to a self-detection method and device for goods shelf settlement, and provides the following scheme: obtaining a top view image through an image sensor arranged right above the top of a goods shelf, dividing the image into a plurality of grid units, and positioning a rectangular geometric shape by utilizing Hough transform; and screening a plurality of to-be-detected areas in combination with the edge features. For an area to be measured, homographic registration and ortho-rectification are carried out based on a reference image, a displacement field is obtained by adopting sub-pixel-level dense registration, and a geometric parallax component field corresponding to imaging parameters is obtained through robust estimation. And under the hypothesis of small deformation, inverting the parallax into a pixel normal distance, and carrying out weighted aggregation on the local region to obtain a local distance measurement result. And by iteratively combining adjacent grids, determining a settlement area boundary, and finally outputting a settlement detection result. Millimeter-level settlement quantification can be realized under a single-frame image, hardware transformation is avoided, and the method is suitable for automatic detection and long-term monitoring of multi-specification goods shelves.

The invention discloses a space-time speckle projection three-dimensional imaging method based on multi-frame optical flow alignment. Firstly, a projector based on DLP is used for projecting a space-time speckle pattern to a measured scene, and a binocular camera synchronously collects a three-dimensional space-time speckle image. The calibration parameters of the binocular camera are used to carry out stereo correction on an acquired original speckle image, and a parallax image is generated frame by frame in combination with a coarse-to-fine single-frame speckle matching strategy. And estimating a two-dimensional inter-frame displacement field between continuous disparity maps by using an optical flow method by taking an intermediate frame disparity map as a reference, compensating motion artifacts in a space-time speckle image, and ensuring strict space-time registration of a dynamic target. And based on the speckle image after motion correction, a speckle matching strategy is expanded to a time-space domain, and high-precision multi-frame three-dimensional measurement of a complex dynamic scene is realized. The method is suitable for performing rapid and high-precision three-dimensional modeling on a moving target in an unstructured environment, and can perform accurate three-dimensional measurement on a high-speed dynamic target undergoing any translation or rotation motion.

Embodiments of the present disclosure relate to surface estimation using stereo imaging and surface disparities. For example, a surface disparity field representing a surface in the environment (e.g., the ground) may be estimated from stereo image data and used for various downstream tasks. For example, the difference between a stereo disparity field and a ground disparity field may be used to detect objects, a representation of a navigable space may be generated by radially casting 2D rays in the ground disparity field, the ground disparity field may be used to compensate ego-motion for high dynamic attitude changes, and / or the ground disparity field may be lifted to 3D and used to fit a surface profile to points sampled from the lifted point cloud.

The invention relates to a naked eye 3D binocular image acquisition and real-time processing system based on hardware synchronous triggering, and belongs to the technical field of image processing and three-dimensional display. According to the system, a hardware synchronous triggering mechanism is adopted, a time sequence synchronous control unit is used for sending a synchronous pulse signal to a binocular image sensor, and strict synchronization of left and right viewpoint image acquisition is ensured. The image signal processing unit processes collected original data, the stereo parallax correction module performs epipolar correction, and the sub-pixel interleaving module generates a composite view frame according to grating parameters of the display terminal. The system realizes high-speed data transmission through a double-buffer direct memory access DMA mechanism. The problems of visual tearing and weak stereoscopic impression caused by asynchronous binocular image acquisition in the prior art are solved, nanosecond-level synchronization precision is realized, optical crosstalk is reduced, and smoothness and comfort of stereoscopic display are ensured.

The invention discloses a steel bar spacing measurement method and system based on multi-view vision, and relates to the field of distance measurement, in the method, based on remapping parameters, a stereo correction module carries out stereo correction on left and right images to obtain corrected left and right images; based on the global features of the corrected left and right images, a reinforcement depth information calculation module calculates a feature matching constraint matrix; based on the corrected local feature points of the left and right images, a reinforcing steel bar depth information calculation module determines matched feature point pairs; based on the matched feature points, a steel bar depth information calculation module calculates a parallax value and calculates depth information of a steel bar intersection point according to the parallax value and a preset camera calibration parameter; based on the corrected left and right images, a reinforcing steel bar intersection point three-dimensional coordinate reconstruction module detects and reconstructs pixel coordinates of reinforcing steel bar intersection points; and based on the depth information and the pixel coordinates, the physical spacing calculation module calculates the spacing of the reinforcing steel bars according to an inverse projection formula. The method is used for improving the accuracy of steel bar spacing measurement.

In various examples, systems and methods are disclosed relating to determining first track point heights of a ground surface for each of a plurality of frames of a disparity image based on a plane parallax algorithm, the first track point heights including previous track point heights of the ground surface for each of the at least one previous frame of the plurality of frames of the disparity image and current track point heights of the ground surface for the current frame of the plurality of frames of the disparity image and determining second track point heights by temporally fusing the current track point heights for the current frame and the previous track point heights for each of the at least one previous frame.

The invention discloses a semantic scene completion method and device, electronic equipment and a readable storage medium. The method comprises the following steps: acquiring a binocular image; performing depth estimation processing on the binocular image to obtain a multi-scale image feature map, a disparity probability distribution map and a disparity map of the monocular image; performing conversion processing from a parallax dimension to a depth dimension on the parallax image of the monocular image to obtain a depth image of the monocular image; processing the multi-scale feature map and the depth map of the monocular image to obtain a first semantic feature map of the monocular image; performing depth feature extraction processing on the parallax probability distribution diagram of the monocular image to obtain a depth probability distribution diagram of the monocular image; and determining voxel occupation data and voxel semantic data of the semantic occupation data based on the depth map of the monocular image, the first semantic feature map and the depth probability distribution map so as to perform semantic scene completion. According to the invention, semantic scene completion can be carried out based on visual image data.

The invention discloses a star map registration method based on a remote optical image, relates to the technical field of image processing, and solves the problems that the existing method is multi-oriented to a single telescope, most of the single telescope is aligned at a star point level, and the robustness is insufficient when parallax, distortion, optical difference and background pollution exist in remote multi-station imaging. The method comprises the following steps: acquiring a remote star map and extracting a star point centroid; angular distance calculation and triangle construction; registering the centroids of the star points in the whole image; performing similarity transformation and homography estimation; and carrying out sub-pixel refinement and full image registration. According to the invention, dual registration of star point centroids and pixel coordinates can be realized for star maps shot by a plurality of telescopes in different places, and meanwhile, a high-quality registration reference can be provided for subsequent three-dimensional information acquisition of a space target and identification and positioning of the space target.

The invention provides a binocular vision global positioning system and method for a mobile robot, and relates to the technical field of robot vision navigation, and the method comprises the steps: carrying out the adaptive exposure compensation of binocular images of a left camera and a right camera, extracting edge contour feature points irrelevant to illumination, and generating a high-quality depth feature map through the combination of parallax calculation; meanwhile, feature units are constructed according to the inflection points, so that the global position of the mobile robot is determined. Therefore, the problem that the global positioning precision is reduced due to unstable visual feature extraction caused by rapid change of illumination intensity of the mobile robot in a multi-region switching scene can be solved to a certain extent.

The invention provides an AI human shape recognition perception system and method based on binocular vision, and the method comprises the steps: carrying out the real-time collection through a binocular camera when a doorbell key is triggered, and carrying out the preprocessing of an original image collected in real time; performing coarse parallax estimation on the real-time image rectification to obtain a full-field coarse depth map, determining a human shape candidate region list by using the full-field coarse depth map and combining the heat source region of interest, and performing fine parallax estimation on the human shape candidate region list to obtain a fine depth patch; converting the corresponding fine depth patch into a three-dimensional point cloud set according to the pose information, and performing scale prior screening based on the corresponding three-dimensional point cloud set to obtain a plurality of human shape candidate reserved areas; and performing fusion identification according to the extracted multi-modal features to obtain a human shape identification result. According to the technical scheme provided by the invention, layered parallax estimation and three-dimensional scale prior screening can be carried out on the real-time image to realize high-reliability human shape recognition under the condition of low power consumption, so that the recognition reliability of a sensing system is improved.

The invention discloses a binocular thermal imaging image fusion method based on dynamic compensation, and relates to the technical field of infrared imaging, a dynamic compensation operation module is constructed, a pixel displacement matrix of a right eye image is generated according to a real-time position deviation value, real-time geometric correction is performed on the right eye image before the image is output, and the image fusion precision is improved. Through a real-time dynamic registration and progressive fusion mechanism, the problem of ghosting in binocular thermal imaging observation is effectively solved, a thermal radiation feature extraction and cross-channel synchronous analysis technology is adopted, the feature recognition bottleneck of a traditional visible light registration method in a thermal imaging scene is broken through, and the real-time dynamic registration and cross-channel synchronous analysis technology is achieved. In combination with a dynamic offset compensation and temperature adaptive progressive fusion algorithm, sub-pixel-level parallax correction is realized while the integrity of original thermodynamic data is maintained, and continuous ghosting interference caused by binocular image space deviation during human eye observation is eliminated. And real-time observation requirements of targets with different distances can be met without modifying an optical hardware structure.

The invention relates to the technical field of three-dimensional reconstruction, and discloses a mark point region priority processing-based three-dimensional scanner rapid reconstruction method, which comprises the following steps of: configuring a plurality of mark points in a region range of a target to-be-measured object, and collecting left and right images of the target to-be-measured object; identifying mark points in the left image and the right image, and extracting two-dimensional image coordinates of each mark point; performing region division on the left and right images based on the center point; performing feature extraction and stereo matching processing on a target image corresponding to the region of interest; calculating a local three-dimensional point cloud of each mark point in the region of interest according to the local disparity map, and analyzing camera poses under a plurality of target view angles according to the two-dimensional image coordinates and the local three-dimensional point clouds; converting the local three-dimensional point cloud to a preset world coordinate system according to the camera pose; and reconstructing a three-dimensional model of the target object to be measured according to the three-dimensional point cloud data under the plurality of target viewing angles. According to the invention, the reconstruction efficiency of the three-dimensional scanner can be improved.

The invention relates to the field of image processing, in particular to a visual image processing method and device, equipment and a program product. The method comprises the following steps: acquiring a binocular image, and generating a first disparity map through a stereo matching network; obtaining a second disparity map through extreme value filtering; generating an edge mask through edge detection; performing edge filtering on the second disparity map according to the edge mask to obtain a third disparity map; and horizontal displacement is obtained according to a parallax value in the third parallax image, parameters are calibrated through a camera, the horizontal displacement is converted into depth information, and a three-dimensional point cloud is generated according to the positions of the pixel points and the depth information. According to the method, a real boundary is extracted through edge filtering, parallax of a boundary area is forcibly corrected by using an edge mask, a transition zone of network prediction is suppressed, burrs or outliers of point clouds after conversion can be effectively reduced, scattered point cloud noise is eliminated, the object contour boundary is clearer, and the perception precision of a visual system is improved.

The invention relates to the technical field of endoscopes, and provides a spectral image processing method for a three-dimensional endoscope. The method comprises the following steps: synchronously acquiring single-band spectral images returned by multiple sensors of the endoscope; after the single-band spectral image is corrected, a two-dimensional spectral image is generated by combining multi-level fusion of the spectral weight; constructing a three-dimensional point cloud coordinate set through parallax calculation; mapping the two-dimensional spectrum fusion image to a three-dimensional point cloud based on a back projection sub-pixel mapping algorithm to obtain a three-dimensional spectrum point cloud; and performing Poisson fusion driven inter-block splicing fusion on the three-dimensional spectrum point cloud, and outputting an interactive three-dimensional navigation model. The technical problem that image details are lost and three-dimensional reconstruction is inaccurate due to the fact that spectral image fusion precision is insufficient in an existing three-dimensional endoscope image processing method is solved, registration and reconstruction of high-precision three-dimensional spectral point clouds are achieved through multi-modal image collaborative correction and optimization fusion, and the image fusion precision is improved. And the accuracy and the real-time performance of navigation in the endoscope are improved.

The invention provides an image fusion stereoscopic display method and system based on a Unity engine, and relates to the technical field of computer graphics and virtual reality. According to the method, a left-eye camera and a right-eye camera are configured in a Unity scene, left and right view angle images are collected according to interpupillary distance parameters, and left-eye and right-eye rendering textures are generated; generating a UI texture according to the Canvas type of the UI element, executing parallax compensation, pixel alignment and image fusion processing through a Compute Shader, and superposing image layers according to the transparency of the UI texture to generate a synthetic display image; and introducing a previous frame result into the fused image, and realizing time continuous output based on an inter-frame smooth function. And outputting the synthesized texture to a device supporting a plurality of stereoscopic display modes through a graphic rendering pipeline. According to the method, efficient fusion of the 3D image and the UI is realized, the rendering efficiency and the visual immersion are improved, and the method is suitable for scenes such as virtual reality, augmented reality and digital twinning.

The invention discloses a power transmission channel obstacle positioning method and system based on binocular vision and COLMAP, and relates to the technical field of intelligent inspection and three-dimensional space perception, and the method comprises the steps: collecting a left image pair and a right image pair of a power transmission channel, carrying out the preprocessing of denoising, distortion correction and image enhancement, generating a depth map through parallax calculation based on the preprocessed image pair, and carrying out the positioning of the obstacle in the power transmission channel. Performing feature extraction and matching, sparse point cloud generation and dense point cloud reconstruction, outputting a three-dimensional dense point cloud model of the power transmission channel, segmenting an obstacle region from the dense point cloud model, and calculating the spatial position and size of an obstacle and the distance between the obstacle and the power transmission line through geometric model fitting. And the obstacle risk level is evaluated according to the distance and the size to generate a positioning result. According to the invention, full-process automation from data acquisition to risk early warning is realized, the problems of low efficiency and large error of traditional manual inspection are solved, and reliable technical support is provided for safe operation and maintenance of the power transmission line.

A cross-modal binocular vision depth estimation method based on contrast learning comprises the following steps: collecting cross-modal image data of monocular alignment, collecting RGB images and non-RGB images through a multi-modal camera system, and performing strict camera calibration to realize alignment of pixel levels; a cross-modal binocular data generation model is constructed, binocular image data meeting the standard is generated based on cross-modal image data of monocular alignment, and a parallax transformation and edge perception restoration module based on depth is included; constructing a cross-modal binocular depth estimation model, introducing feature pre-training and supervised constraint optimization based on comparative learning, and training by using an aligned monocular cross-modal data set and a generated cross-modal binocular data set; and storing the training parameters, and generating a parallax image according to the input cross-modal binocular data. According to the invention, the accuracy of the binocular depth estimation model is improved by generating the cross-modal data, and the stability of the cross-modal depth estimation method is improved from the perspective of the model and the generated data.

The invention discloses a real-time ultra-high-definition interactive naked-eye 3D display content synthesis method, which comprises the following steps of S1, firstly, modeling interactive content, such as buildings, mechanical equipment, game scenes and the like, and converting mechanical and building models and the like into a. Fbx format by means of a. Step file format in a unified manner; s2, completing model processing in professional model processing software such as 3DsMax and the like: unifying coordinate axes, and performing surface reduction on the model; and S3, building an interaction scene in the Unity 3D based on the processed model. And S4, for a scene and a model needing to be displayed, generating a virtual parallax camera equivalent to off-axis photography, and controlling the shooting parameters of the parallax camera. And S5, performing hybrid synthesis on the multi-view parallax image based on the texture bitmap, calculating large-scale pixels based on a calculation shader, and shifting a GPU idle time sequence in a Unity 3D script process, and then uniformly entering a rendering assembly line to complete rendering and synthesis of the whole scene. And S6, developing interaction input logic according to different object interaction requirements. The invention provides a calculation three-dimensional display algorithm based on a texture bitmap, ultra-high-definition naked-eye 3D display content can be synthesized in real time under Unity 3D, and a better 3D display effect can be obtained by combining technologies such as equivalent off-axis photography and the like. In addition, the invention also provides a display efficiency optimization method based on a calculation shader, so that the system can run on a lower-configuration host platform, and the problem of higher hardware requirements for real-time ultrahigh-definition naked-eye 3D display content synthesis while the interaction requirements are met is solved.

The invention relates to a plate spring center point visual positioning method based on multi-model cooperation, and belongs to the technical field of plate spring center hole machining. Comprising the following steps: S01, acquiring a plurality of images under different exposure parameters, and fusing the multi-exposure images by using an IFCNN model to obtain an image with moderate exposure; s02, a YOLOV8 model is adopted to carry out target detection on the image, all the plate springs are accurately recognized, ROIs (Regions of Interest) of the plate springs are extracted, and each ROI only comprises a single plate spring; s03, performing fine segmentation by using U-Net, and extracting an accurate contour of a single plate spring; and S04, a binocular vision system is adopted, precise three-dimensional positioning of the center point of the plate spring is achieved through double-camera parallax calculation, and space coordinates (X, Y and Z) of the center point of the plate spring are obtained. According to the method, the space coordinates of the center point of the plate spring are accurately obtained in the plate spring punching process by combining the target detection and semantic segmentation methods, and automatic center punching of the plate spring plate is conveniently achieved.

The invention discloses a multi-modal double-camera face depth detection method and system, and relates to the field of image recognition. The method comprises the following steps: S1, calculating a parallax deviation value through multi-mode double-camera synchronous acquisition image information, and outputting an aligned image set after interpolation; s2, on the basis of the aligned image set, performing preliminary judgment by calculating a multi-modal topology tension factor and a geometric expansion degree of a feature map and fusing to generate a modal coordination expansion coefficient; s3, generating a face structure three-dimensional point cloud according to the aligned image set, and calculating a multi-modal evaluation index; and S4, calculating a skin authenticity index according to the aligned image set, constructing an authenticity confidence scoring function in combination with the modal coordination expansion coefficient, the multi-modal evaluation index and the skin authenticity index, and performing authenticity discrimination. By comprehensively evaluating the facial structure, texture and heat distribution, the accuracy and robustness of living body detection are effectively improved, and the method adapts to high safety requirements in various environments.

The invention belongs to the technical field of trajectory measurement, and particularly relates to a three-dimensional tracking and measuring method and system for a fine high-speed object, which provides stable parallax information input through the steps of binocular video acquisition, target detection and tracking, parallax calculation and three-dimensional positioning, and three-dimensional trajectory reconstruction and measurement analysis, and provides stable parallax information in image processing. By combining high-precision target detection and a time sequence tracking algorithm, the recognition and tracking stability of a high-speed fine target is improved, the problems that target detection is difficult and parallax matching is inaccurate are solved, parallax calculation is carried out by utilizing the pixel position difference of the target in left and right images and double-target calibration parameters, and three-dimensional coordinates are quickly recovered. The processing efficiency and the real-time performance are remarkably improved, the technical defects that an existing process is complex and the response delay is large are overcome, and the method is suitable for scenes such as ball training and competitive analysis which have high requirements for high-speed measurement precision and the real-time performance.

The invention discloses a stereoscopic vision optimization method and system for a naked-eye 3D large screen, and particularly relates to the technical field of naked-eye 3D vision optimizing.The method comprises the steps that environment illumination and audience positions are sensed in real time through multi-sensor fusion, and an environment light field model is established; glare crosstalk noise is predicted based on physical simulation, and self-adaptive suppression and compensation are carried out in combination with human eye visual sensitivity and image content features; a virtual camera is dynamically generated according to the real-time positions of the eyes of the audience, and a lightweight neural radiation field renderer is used for real-time re-rendering, so that motion parallax is realized; and finally, intelligently fusing the glare compensation layer and the perspective correction layer, coding and outputting to a screen. The system correspondingly comprises an environment perception module, a glare compensation module, a perspective rendering module and a fusion coding module. The naked-eye 3D large-screen display method effectively inhibits ambient light interference, improves the quality and immersion of a stereoscopic picture under different visual angles, and is suitable for naked-eye 3D large-screen display under outdoor and complex illumination environments.