40 results about "Binocular stereo" patented technology

This application belongs to the field of computer vision and optical measurement technology, specifically disclosing a point cloud stitching method and apparatus based on monocular pose prior marker matching. The method includes: calculating the pose of multiple markers extracted from left and right camera images, determining the normal vector and three-dimensional coordinates of each marker's circular cross-section in its respective camera coordinate system; transforming the three-dimensional coordinates and corresponding normal vectors of each marker in either the left or right camera image to the other camera coordinate system for marker point registration between the left and right camera images; the circular cross-section is a circular cross-section in three-dimensional space with the origin of the camera coordinate system as its vertex, passing through the elliptical curve where the marker is located; and stitching the three-dimensional point cloud of markers based on the marker point registration results of the left and right camera images. This application can significantly improve the accuracy of binocular stereo marker matching and the system's anti-interference capability in complex industrial scenarios.

The application discloses a kind of environment simulation method and system based on binocular stereo vision measurement, it is related to scene simulation technical field, and its technical solution points are: the method includes by constructing the physical imaging model in left and right optical elements in binocular stereo vision camera, and left and right view is obtained based on the physical imaging model;Determine the disparity map between the left and right view, determine scene depth image based on the disparity map;Three and more scene depth images generated by three and more different binocular stereo vision cameras corresponding to the scene are acquired, and the three and more scene depth images are fused, to construct the three-dimensional simulation model corresponding to the scene based on the depth image after fusion.The application can accurately reflect the depth level and spatial relationship of scene, and the three-dimensional simulation model finally constructed is more realistic, and can strongly support virtual reality, three-dimensional measurement and other applications.

The application provides a mechanical arm grabbing method and system based on cooperation of large field of view and local vision, and relates to the technical field of robot vision recognition. The system comprises an unmanned ship platform, a five-degree-of-freedom mechanical arm, a large field of view vision module, a local vision module and a control module; the large field of view vision module realizes wide range search and tracking of a sea surface target through a spherical camera at a base, guides the unmanned ship to approach, and the local vision module acquires target depth and three-dimensional coordinates by means of binocular stereo cameras of end grippers. The application combines YOLOv8 detection, Kalman filtering and forward dynamics compliant control algorithm, realizes cooperation of the large field of view and the local vision, completes the whole process automation from long-distance target discovery to close-range accurate grabbing, and effectively improves the recognition accuracy and grabbing success rate of the mechanical arm on the sea surface environment on targets such as floating balls and ropes.

The application discloses a PCB solder paste printing three-dimensional defect detection system based on multispectral imaging, and relates to the field of machine vision detection.The technical scheme points of the application include a multispectral image acquisition module, a four-channel industrial camera based on RGB and near-infrared, and a tunable LED light source array; the reflection characteristic data under different penetration depths are acquired through a wavelength switching mechanism; a motion control trigger module is based on a servo motor driven XYZ three-axis object table, and positioning is realized in cooperation with an encoder feedback; a pulse width modulation signal is adopted to coordinate the camera shutter and the platform moving speed; the application realizes the dual verification of material composition quantitative analysis and three-dimensional topography reconstruction through the combination of the four-channel imaging of RGB and NIR and the Beer-Lambert law modeling, and avoids the limitations of monocular vision; the cross-frame data alignment is realized through the projection of a structured light and a binocular stereo matching technology in cooperation with an ICP algorithm, and the details defects can be better detected.

This invention discloses a portable binocular stereoscopic imaging device based on a single camera, applicable to the field of medical aesthetics. The device comprises an image acquisition component, a supplementary lighting component, and a laser locator. The image acquisition component receives images of the subject reflected from optical paths in two directions, thereby performing 3D modeling. The supplementary lighting component has a mirror angle identical to that of the image acquisition component, ensuring the supplementary lighting angle matches the shooting angle, allowing for uniform illumination of the subject, enhancing lighting, and eliminating shadows. The laser locator allows for adjusting the angle of the laser emitter to set different shooting distances for different subjects. This invention achieves single-camera binocular stereoscopic imaging while not only providing more uniform supplementary lighting but also enabling more convenient adjustment of the shooting distance.

This application provides an optical lens, a camera module, and a binocular stereo vision system. The optical lens, used in the binocular stereo vision system, includes multiple lenses, specifically at least eight lenses and a filter. Each lens has a different temperature coefficient of refractive index (dn / dT) to compensate for thermal defocusing when the temperature changes, thereby maintaining the total focal length of the optical lens within a preset range. Here, n is the refractive index of the lens, and T is the temperature. This optical lens achieves a balance of large field of view, high resolution, and clear imaging over a wide temperature range.

The application belongs to the technical field of medical treatment and can be used for sample data enhancement in the scene of human body, tissue organ modeling and the like in the medical field, and particularly relates to an image data enhancement method, a training method and device of a binocular stereo matching model. The method comprises the following steps: obtaining a target sample image pair, the target sample image pair comprising a first image and a second image; generating a first random mask and a second random mask; obtaining a first disordered image and a second disordered image; obtaining a first data enhancement image based on the first random mask, the second disordered image and the first image; obtaining a second data enhancement image based on the second random mask, the first disordered image and the second image; and combining the first data enhancement image and the second data enhancement image to obtain a data enhancement sample image pair. The above method and device improve the adaptability of the introduced noise to the training sample set, so that the expanded training sample has better training effect.

This invention discloses a visibility estimation method and apparatus based on binocular vision. The method includes: simultaneously acquiring left and right views using a calibrated binocular camera; inputting the image pairs into a stereo matching deep neural network to obtain a disparity map and converting it into a depth map; inputting the left view and depth map into a dual-branch deep convolutional neural network to extract multi-scale features; fusing RGB features and depth features through a cross-modal feature fusion module; and finally outputting a visibility estimate through a feature aggregation and regression module. The apparatus includes a binocular image acquisition unit, a data processing and visibility estimation unit, and a result output unit. This invention solves the depth ambiguity problem of monocular vision by fusing binocular depth information and image appearance information, achieving high-precision, non-contact visibility surface measurement. It has the advantages of low cost and flexible deployment, and is suitable for visibility monitoring in traffic scenarios such as highways.

The present application belongs to the field of robot technology, and particularly relates to a whole vehicle assembling robot precision grabbing method based on binocular stereo vision, which comprises the following steps: collecting a part image to be grabbed to generate a depth map, using an adaptive window to carry out distance weighted interpolation repair on invalid pixels to obtain a point cloud set; calculating a surface smoothness index of a candidate point; obtaining effective candidate points through edge distance screening and cylindrical virtual space collision detection; combining effective point cloud density, surface smoothness index and edge distance to calculate a grabbing suitability; selecting an optimal grabbing point according to the grabbing suitability and controlling a robot to perform grabbing. The present application effectively solves the data loss and noise interference problem caused by high light reflection surface, and improves the stability and safety of grabbing operation under complex lighting environment.

This invention discloses an autonomous sensing robotic arm suitable for confined spaces. A lateral translation slide rail is mounted on the upper end of a compact equipment mounting base, allowing for reciprocating movement along the length of the base. A second-stage rotation unit is mounted on the first telescopic arm, enabling second-stage horizontal rotation adjustment of the second telescopic arm and cooperating with the first-stage rotation unit to achieve horizontal positioning. A binocular stereo vision sensor, mounted on the second telescopic arm, performs real-time 3D ranging, identifies unexpected obstacles within the work area, and generates a 3D point cloud of the local environment, providing environmental perception data for obstacle avoidance and path planning. This invention improves operational flexibility, ensures operational continuity, significantly increases overall operational efficiency, enhances operational reliability, and significantly reduces the requirements for operator skills and experience.

This invention relates to the field of bamboo product processing, specifically to the optimization of a method for the bamboo product feeding process. The purpose of this invention is to provide an optimal target recognition method suitable for the automatic, one-by-one feeding of bamboo products. Based on binocular stereo vision, it simultaneously acquires two-dimensional images and three-dimensional depth information of the scene, autonomously determining the optimal object to be grasped. This provides a recognition and instruction basis for the subsequent automatic and reliable identification and separation of individual bamboo strips from a chaotic pile of bamboo strips. It facilitates the full automation of the front-end feeding process, seamlessly connecting with downstream processing equipment, and significantly improving the overall automation level and operational efficiency of the production line.

This invention discloses a pixel-by-pixel cross-medium 3D measurement method based on a ray model, belonging to the field of optical measurement technology. Addressing the technical challenge of imaging distortion caused by light refraction of the object under transparent media coverage, this method proposes a novel calibration and reconstruction framework that does not rely on precise modeling of medium parameters. By constructing a structured light projection system and utilizing imaging data of a calibration target in multiple height planes, the method independently calibrates the corresponding object-side ray equation for each camera pixel. Combined with binocular stereo matching and pixel-height mapping techniques, it ultimately achieves high-precision 3D surface reconstruction of cross-medium scenes. This invention is applicable to optical measurement scenarios with unknown or complex refractive interfaces, aiming to overcome the bottlenecks of difficult parameter solving and limited accuracy of traditional pinhole models in cross-medium environments, providing an innovative solution for 3D measurement in complex environments such as underwater and inside protective enclosures.

The application provides a face recognition and living body detection fusion method and device based on a binocular camera, and the method comprises the following steps: after collecting original left and right face images, performing binocular image preprocessing to obtain a standard binocular image pair; performing multi-scale stereo feature extraction on the standard binocular image pair to obtain a depth-texture joint feature representation and a disparity map; combining the disparity map, performing adaptive 3D face reconstruction and time sequence dynamic feature modeling, and through multi-level living body detection fusion decision and face feature extraction and matching, completing end-to-end fusion verification of face living body detection and face recognition. Through deep fusion of binocular stereo vision and deep learning, multi-dimensional living body discrimination features are constructed, and various known and unknown attacks can be effectively resisted. An adaptive stereo matching and 3D face reconstruction mechanism is designed, the unstable recognition problem caused by illumination change and posture change is overcome, and the system robustness is improved.

This invention relates to a method for detecting foreign objects (FOOs) on airport runways based on biomimetic binocular vision. The method includes: simultaneously receiving images at least two scales from cameras with different focal lengths; performing cooperative target detection based on spatial correspondence; mapping and fusing the detection results to output supervised detection results; employing an unsupervised learning algorithm for anomaly detection and outputting unsupervised detection results; cross-validating and fusing the supervised and unsupervised detection results to generate a comprehensive FEO detection result; receiving left and right view images from a biomimetic binocular camera; performing three-dimensional spatial localization of FEOs in the comprehensive FEO detection result based on a binocular stereo vision algorithm; and fusing the comprehensive FEO detection result with the FEO location information to generate a final detection report. This method integrates multiple technological advantages, forming a complete, high-precision, and robust all-weather FEO detection solution for airport runways.

The application discloses a network distribution vehicle-mounted high-precision positioning method and system based on Beidou and monocular fusion, relates to the technical field of positioning and navigation, and comprises the following steps: obtaining the relative displacement vector of a vehicle in adjacent frames based on a time domain differential carrier phase model; virtually converting adjacent two monocular images into a dynamic binocular stereo vision model based on the relative displacement vector, and obtaining absolute depth information of image feature points; performing catenary fitting on power lines in the image, obtaining physical geometric features of a plane where the power lines are located, and establishing a physical gravity field geometric constraint; obtaining a constraint factor based on the physical gravity field geometric constraint, the time domain differential carrier phase model displacement constraint and the absolute depth information, constructing a tightly coupled factor graph model for optimizing the motion state of the vehicle, solving the tightly coupled factor graph model, and obtaining a fusion solution containing the position, speed and attitude of the vehicle. The application realizes high-precision and high-robustness positioning and attitude determination, and improves the network distribution inspection operation efficiency.

The application provides a kind of accurate detection system and method of slag quantity based on binocular vision, system includes dry slag machine automatic speed measurement module, calculates the real-time running speed of dry slag machine conveying chain plate;Slag quantity detection module, the time sequence alignment of slag layer three-dimensional point cloud reconstructed by binocular stereo vision is carried out, and the volume of slag quantity is calculated;Interference automatic identification module is used to distinguish dry slag machine conveying chain plate structural member and coal slag, and provides higher quality slag layer three-dimensional point cloud data for slag quantity detection module.The application synchronously collects image by binocular stereo vision, reconstructs high-density three-dimensional point cloud of slag layer by combining improved semi-global matching stereo matching algorithm;Further, the volume of accumulated coal slag is accurately calculated by surface gridding based on Delaunay triangulation and scanning line integration method;And by associating the density parameters in coal database, the volume value is converted into mass data, which realizes accurate and quantitative detection of slag quantity from three-dimensional form to quality index.

1. The name of the design product: camera (binocular stereo camera). 2. The use of the design product: binocular stereo camera for vehicle or aircraft. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The application discloses a three-dimensional reconstruction method of a secondary arc based on binocular stereo vision, which comprises the following steps: firstly, a binocular stereo vision system is built, and two high-speed cameras are used to acquire secondary arc images; secondly, an atmospheric scattering model-based defogging algorithm is used to defog and enhance the arc images, and a double-threshold value repair algorithm based on the gray scale of the secondary arc images is used to connect the discontinuous arcs; then, a semi-global stereo matching method is used to calculate the disparity of the corresponding points in a pair of images, and a weighted least square method is used to optimize the disparity map; finally, the three-dimensional coordinates of the arcs are calculated according to the triangulation principle. The application can obtain clear and continuous three-dimensional images of the secondary arcs and accurate real physical parameters of the secondary arcs, and has important significance for the subsequent research on the motion characteristics and discharge evolution process of the secondary arcs.

The present application relates to the field of image processing, and provides a kind of image depth estimation method, device, equipment, medium and computer program product, left and right eye images including left eye adjacent frame image and correction binocular image are input into depth estimation model including space-time information extraction network, binocular stereo matching network and depth evaluation network to obtain depth map;Space-time information extraction network is used to carry out space-time feature extraction to left eye adjacent frame image, obtain binocular pose transformation information and image change information between adjacent frame image;Binocular stereo matching network is used to carry out multi-layer feature extraction to correction binocular image, obtain multi-level parallax map;Depth evaluation network is used to evaluate binocular camera pose transformation information, image target change information and multi-level parallax map, obtain the depth map of left and right eye images.The present application improves the precision of image depth evaluation by learning the dynamic change rule between binocular image frames, using motion information and time sequence consistency in dynamic scene.

The application discloses a fire source recognition and positioning system of a fire-fighting robot based on binocular vision and thermal imaging, a binocular depth camera acquires binocular stereo images and structured light images in a target scene, records visual information, a thermal imager acquires thermal images and temperature data under the same scene, space registration is performed on the acquired binocular stereo images, structured light images and thermal images, so that the three are aligned under the same coordinate system, the binocular stereo images, the structured light images and the thermal images are fused, and the fused images are processed, the processed fused images are input into a trained fire source recognition network model for detection, after a preliminary fire source point is detected, a temperature value is compared with a preset temperature threshold value, if the temperature value exceeds the preset temperature threshold value, the fire source is determined, binocular imaging triangulation and structured light positioning fusion algorithms are used for fire source positioning, and the application has the advantages of quick fire source positioning and quick fire extinguishing.

This invention discloses a vehicle emergency braking system and its decision control method and apparatus. The decision control method includes: acquiring obstacle information through a binocular stereo camera and millimeter-wave radar; determining a first dynamic weight for the first data acquired by the binocular stereo camera and a second dynamic weight for the second data acquired by the millimeter-wave radar, based on the current obstacle type, environmental parameters, and distance level; weightedly fusing one or more obstacle-related parameters according to the first data, the second data, the first dynamic weight, and the second dynamic weight to obtain fused data; obtaining a decision processing result based on the fused data and the vehicle status data synchronously transmitted via the vehicle's CAN bus; and determining the output control command based on the decision processing result. Using this scheme can improve perception accuracy, enhance the accuracy of emergency braking, effectively reduce the likelihood of traffic accidents, and ensure vehicle driving safety.

This invention discloses a vision-based intelligent sorting system and method for multi-joint robotic arms. It replaces binocular stereo matching with monocular vision and motion prediction, eliminating the need for a PLC intermediate layer to construct a native control architecture for the robotic arm. A layered software architecture comprising a vision processing layer, a motion planning layer, and a control execution layer achieves a closed-loop process from perception to decision-making to execution. Vision processing integrates background subtraction and optical flow methods to achieve dynamic target tracking and pose calculation. Motion planning, based on transmission linear velocity and visual positioning data, predicts the grasping point and generates a smooth trajectory. The control execution layer employs an adaptive fuzzy PID algorithm to dynamically adjust parameters, eliminating mechanical vibration and improving trajectory tracking accuracy. This invention effectively solves the problems of visual processing delay, insufficient dynamic tracking accuracy, and poor environmental adaptability in traditional sorting systems, and can be widely applied in industrial scenarios such as electronic component sorting, logistics parcel sorting, and waste material recycling.

The application discloses a binocular stereo matching hardware architecture supporting variable disparity range, which can realize real-time switching of disparity working range in work by configuring a cost calculation and aggregation module through a disparity range switching controller without changing algorithm processing details, can switch the disparity range worked by hardware according to different application scenarios, performs different disparity range calculation in different working scenarios, and supports a working environment requiring a large disparity range while the hardware can work in a small disparity range mode in an open outdoor scene, so that the calculation amount is greatly reduced, and the working power consumption of the overall hardware is reduced.

This invention discloses a low-latency visual perception and decision-making system and method for a table tennis robot. The system includes: a perception layer comprising a binocular stereo camera and a target detection unit. The binocular stereo camera acquires image sequences of the table tennis ball at a frame rate of not less than 200 Hz. The target detection unit identifies the target in each frame and outputs the original position and confidence level of the table tennis ball through stereo triangulation. A cascaded observation layer comprising an SG filter and an aerodynamic EKF module. The SG filter performs analytical differentiation on the position sequence within a sliding window to generate a virtual velocity observation. The aerodynamic EKF module fuses the original position and virtual velocity observations and outputs an optimal state estimate including position, velocity, and acceleration. A decision support layer comprising a physics-driven deterministic finite state machine detects key tactical events, including landing point and net crossing, and outputs trajectory prediction streams and event trigger signals to the control layer of the table tennis robot.

This invention discloses a robust stereo matching method based on feature pyramids and attention perception, comprising: setting a feature extraction pyramid to process the input binocular stereo image, and obtaining multi-scale feature maps of the left and right view input images respectively; constructing a multi-scale cost volume pyramid using the multi-scale feature maps, and implementing feedback interaction and cross-scale cost aggregation between cost volumes of different scales; converting the cost volume pyramid into a probability value pyramid using a softmax function, and processing the probability value pyramid using a soft-argmin function to generate an initial disparity map; designing a saliency attention perception module to extract and generate attention feature maps in the shallow layers of the stereo matching network, and fusing the feature maps with the initial disparity map to obtain a refined disparity map. This invention can effectively correct erroneous matching points, restore lost image details and sharp object edges, improve the robustness and precision of disparity prediction, and generate a fine and accurate disparity map.

The application discloses a park landscape water body water quality sensing early warning management method and system, belongs to the technical field of water quality monitoring and landscape management, and comprises the following steps: collecting water surface multi-spectrum images and binocular stereo images of a park water body to form a time-synchronized multi-view image sequence; constructing a three-dimensional space coordinate of a water body surface according to the multi-view image sequence; mapping each band reflectivity on the three-dimensional coordinate to obtain a water body surface reflectivity spatial distribution map; extracting a water body appearance index vector according to the water body surface reflectivity spatial distribution map; establishing a correlation between reflectivity and water quality optical indexes, and inversely solving a water quality optical index vector; calculating a consistency deviation value of the water body appearance index vector and the water quality optical index vector, judging whether the indexes exceed a preset early warning threshold value, and outputting an early warning message if the indexes exceed the preset early warning threshold value; and outputting a management strategy according to the early warning message. The application avoids external interference through non-contact sensing, and reduces the false alarm rate through appearance and water quality optical double determination.

This invention discloses a method and apparatus for fine-tuning a sampling robotic arm based on binocular stereo vision 3D reconstruction. The implementation system of this invention comprises: a binocular camera (1), a multi-joint traction robotic arm (2), a sampling device (3), and a sampling device (4). The binocular camera captures images of the sampling area, and the sampling area is reconstructed using binocular stereo vision to obtain a point cloud. Based on the spatial information contained in the point cloud, the target pose of the sampling device at the sampling point is determined, which is then used for the robotic arm's traction. To overcome the problem of significant deviation in robotic arm traction, this invention compares the difference between the actual pose of the sampling device and the target pose, and uses 3D point cloud analysis to provide reference indicators for operator evaluation and adjustment. This invention can assist operators in quickly and accurately fine-tuning the sampling robotic arm during sampling tasks, thereby improving sampling efficiency and quality.