250 results about "Stereo cameras" patented technology

A modeling method for three-dimensional real-time measurement reconstruction, comprising: on the basis of a three-dimensional camera, a laser radar, and an infrared sensor device, generating a multi-source original data set; performing data preprocessing; performing feature extraction and data fusion; performing three-dimensional space construction; by means of a deep machine learning algorithm, performing real-time dynamic adjustment and optimization on a model; and, by adopting an advanced image processing algorithm, generating a high-precision three-dimensional model.

A pest control system is disclosed comprising an optical, computational, and monitoring subsystem, optionally mounted on a mobile platform. The optical system may include a neutralizing laser or multi-wavelength light source, discovery and detail cameras (optionally stereo), a beam-steering mechanism, tunable focus, and optional thermal or depth sensors. The processor, such as a GPU or FPGA, identifies insect or biological targets, adjusts laser focus by depth, and controls beam activation. A monitoring system verifies safety by detecting humans or other non-target entities using environmental and thermal cameras; if detected, laser firing is inhibited. The mobile platform may use wheels, propellers, tracks, or cables, with GPS and data links for remote control. A visible light pre-flash may induce a blink reflex before firing. In some embodiments, a scouting drone transmits target coordinates to the neutralization unit, enabling coordinated, efficient, and safe laser-based pest control.

The invention belongs to the technical field of automatic assembly, and discloses an automatic assembly system and method for a large nut of a water turbine ball valve, and the system comprises a mechanical arm, an end effector and an intelligent nut tightening control system. The end effector integrates an electromagnet adsorption mechanism, a servo drive rotating mechanism, a floating compensation mechanism and a visual recognition mechanism, nuts of different specifications are grabbed in a self-adaptive mode through an electromagnet, submillimeter-level accurate positioning is achieved through a laser galvanometer stereo camera, and the assembling posture is automatically adjusted in combination with the floating compensation mechanism. The intelligent control system adopts a staged tightening strategy, performs real-time monitoring through a torque sensor, and has a dual protection mechanism. The hydraulic turbine ball valve large nut assembling machine achieves full-automatic assembling of hydraulic turbine ball valve large nuts, has the advantages of being high in assembling efficiency, high in positioning precision, high in adaptability, reliable in quality and the like, solves the problems that manual assembling is large in labor intensity, many in potential safety hazards, poor in quality consistency and the like, and remarkably improves the assembling quality and efficiency of key parts of a hydropower station.

The invention relates to the technical field of mining scraper conveyor equipment, in particular to a scraper conveyor chain breakage monitoring method and device based on machine vision. The method comprises the following steps: acquiring a real-time three-dimensional image when a chain moves through a stereo camera; obtaining real-time state data of the chain according to the real-time three-dimensional image; and comparing the real-time state data with standard data, and if the real-time state data does not meet a preset threshold value, determining that the chain has a chain breakage risk. According to the method, the real-time three-dimensional image of the chain during movement is obtained through the stereo camera, the real-time state data of the chain is obtained according to the real-time three-dimensional image, whether the chain breakage risk exists or not is determined by comparing the real-time state data with the standard data, and the chain state can be accurately monitored in real time.

The invention provides a bonding wire defect detection method based on deep learning, which can be used for identifying the defect type of a bonding wire and automatically detecting the bonding quality problem of the wire in an integrated circuit product, and aims to solve the problems of high labor intensity, low detection efficiency and the like. The process comprises the following steps: establishing a bonding wire acquisition physical platform, acquiring a depth image of a bonding wire through a stereo camera, preprocessing the acquired depth image to enhance the image quality, generating a normal diagram corresponding to the depth image through geometric transformation, and stacking the normal diagram and the depth diagram to obtain a final bonding wire data set. Performing data enhancement on the bonding wire data set to expand the data scale; a Depth-YOLO network model is provided, an input layer of an original YOLO model is reconstructed, and an input feature enhancement module is designed; and finally, training a Depth-YOLO model by using the self-built data set, and carrying out end-to-end bonding wire defect detection by using the model.

A method implemented at an autonomous mobile robot equipped with a fork to carry a pallet. The robot transitions between a first and second piecewise flat floor segments with differing geometries. The robot uses sensor data from sensors such as LIDAR, stereo cameras, GPS, and ultrasound sensors to determine the transition between the first and second piecewise flat floor segments. The fork operates based on parameters that meet reference constraints. When the robot detects that a second floor geometry would cause these parameters to no longer meet the reference constraints, the robot determines new parameters that will satisfy the reference constraints. Control signals are then sent to adjust the fork's operation as the robot transitions to the second floor segment.

A multi-modal stereo vision system includes one or more stereo vision units. Each stereo vision unit includes a plurality of stereo camera pairs. Each image pair includes a first image and a second image. The plurality of stereo camera pairs can capture multi-modal image data.

An object detection system for a vehicle that estimates a location of a target object located in an environment surrounding the vehicle includes an ultra-wide band (UWB) sensor network including three or more anchors mounted to the vehicle in wireless communication with a tag mounted to the target object, a non-stereo camera system that captures image data representing the target object located in the environment surrounding the vehicle, and one or more controllers in electronic communication with the UWB sensor network and the non-stereo camera system. The one or more controllers includes one or more processors that execute instructions to fuse together a camera-based location of the target object and a UWB-based location of the target object by a Bayesian filter to estimate the location of the target object.

The invention provides a macrobrachium rosenbergii quality grading system based on machine vision. The macrobrachium rosenbergii quality grading system based on machine vision comprises a prawn body placing platform used for placing macrobrachium rosenbergii to be tested; the three-dimensional acquisition module comprises a structured light projection device, a binocular stereo camera and a flight time depth sensor; and the three-dimensional reconstruction module is used for constructing the data of the three-dimensional acquisition module into a complete three-dimensional point cloud model through a data fusion algorithm and a point cloud registration algorithm. According to the macrobrachium rosenbergii quality grading system based on machine vision, the overall scheme has robustness and expandability, the system is suitable for various large-scale farms and grading scenes, and the intelligent level of macrobrachium rosenbergii quality control is greatly improved.

An electronic device displays a widget dashboard user interface in a three-dimensional environment, displays a representation of a physical tool to as guidance for indicating a location of the physical tool relative to a location associated with video feed, displays suggestions for changing a pose of a camera to a predetermined pose based on image data detected while the camera previously had the predetermined pose, displays a live camera feed and image data and scrubs through the image data in accordance with changes to a pose of the camera relative to a physical object, displays live stereoscopic camera feed with special effects, detects and responds to inputs for virtually annotating portions of objects, and / or displays models of objects and detects and responds to input for rotating and / or viewing the model from different depth positions within the model.

Disclosed herein is a method for estimating a depth of an image. The method may include acquiring a first depth image based on left and right images collected from a stereo camera, estimating a second depth image based on any one of the left and right images, generating a depth estimation model based on first depth values within a depth range recognizable by the stereo camera in the first depth image and on second depth values of the second depth image matching the first depth values, and inputting third depth values of a range intended to be estimated in the second depth image to the depth estimation model, thereby estimating fourth depth values of the first depth image matching the third depth values.

The invention relates to the technical field of mechanical arm obstacle avoidance grabbing, and discloses an automatic obstacle avoidance grabbing system and method. The system comprises a mechanical arm, a stereo camera, a flexible grabbing unit and a control unit, the mechanical arm is arranged on a table top, the stereo camera is arranged on the mechanical arm, the flexible grabbing unit is arranged at the tail end of the mechanical arm, and the stereo camera is used for obtaining point cloud images and plane images of a target object and an obstacle; the control unit is used for obtaining point cloud data of the target object and the obstacle according to the point cloud images and the plane images of the target object and the obstacle, and processing the point cloud data of the target object and the obstacle to obtain the position of a grabbing point; envelope box description is carried out on the mechanical arm, the stereo camera, the flexible grabbing unit and the obstacle so as to carry out self-collision detection and obstacle collision detection, the path from the initial position to the target position is calculated under the condition that collision does not exist, and the mechanical arm is controlled to grab the target object according to the calculated path.

A computer that includes a processor and a memory, the memory including instructions executable by the processor to select first side stereo images of first and second pairs of stereo images acquired at first and second time steps, respectively, and mask first and second first side stereo images, determine point features in masked first and second first side stereo images and determine line features in masked first and second first side stereo images. Matching point features in the masked first and second first side stereo images can be determined using a first attention / graph neural network (attn / GNN) based on keypoints determined based on the line features. Matching line features in the masked first and second first side stereo images can be determined using a second attn / GNN based on keypoints determined based on the line features. Three-dimensional (3D) locations in a scene can be determined by determining stereo disparity based on the matched point features included in the first first side stereo image and point features determined in a first second side stereo image of first and second stereo pairs of images and a 3D stereo camera pose can be determined by determining a perspective-n-point and line algorithm on the 3D locations.

A method for adjusting a depth of a stereoscopic image includes the following. A first disparity correction amount is obtained according to a distance between centers of two lenses of a stereoscopic camera and an interpupillary distance (IPD) of a first observer. A second disparity correction amount is obtained according to a difference between image distances of a stereoscopic display and the stereoscopic camera at zero disparity. A third disparity correction amount is obtained according to the IPD of the first observer and an IPD of a second observer. A stereoscopic image of an object photographed by the stereoscopic camera which has been corrected by the first disparity correction amount, the second disparity correction amount, and the third disparity correction amount is transmitted to the stereoscopic display. A device for adjusting a depth of a stereoscopic image is also provided.

The invention belongs to the technical field of navigation and positioning, particularly relates to a GNSS / visual loose coupling positioning method fusing environmental semantics, and solves the technical problem that a traditional method is insufficient in positioning precision when facing an urban sheltered environment and a high-dynamic scene. According to the method, a GNSS receiver obtains position coordinates of a carrier through a double-difference measurement model of the GNSS receiver, and continuous image frames captured by a stereo camera are transmitted to a VO module for executing pose estimation of the carrier; carrier position coordinates of a GNSS and carrier pose information of a VO module are combined by adopting a loose coupling model, then a shielding factor is calculated according to environmental semantic information and a local mapping module, an adaptive KF algorithm is introduced in combination with the shielding factor, and under the constraint of the shielding factor, the adaptive KF algorithm can calculate an optimal pose estimation value, so that the optimal pose estimation value is obtained. The value is fed back to the GNSS to correct the position coordinate of the carrier, and finally the corrected position coordinate is output as a positioning result.

Methods, systems, and apparatuses, including computer programs encoded on a computer-readable storage medium for estimating the shape, size, mass, and health of fish are described. A pair of stereo cameras may be utilized to obtain off-axis images of fish in a defined area. The images may be processed, enhanced, and combined. Object detection may be used to detect and track a fish in images. A pose estimator may be used to determine key points and features of the detected fish. Based on the key points, a model of the fish is generated that provides an estimate of the size and shape of the fish. A regression model or neural network model can be applied to the fish model to determine characteristics of the fish.

The present disclosure is a data positioning apparatus including a stereo camera which acquires visual data corresponding to 2D and 3D, an inertial measurement unit which acquires inertia data corresponding to acceleration and angular velocity data, and a computing module which receives data acquired from the stereo camera and the inertial measurement unit and performs computation of a visual SLAM engine.

The invention relates to a method for determining the position and / or orientation of tools of construction machines in a construction area, comprising the steps of: attaching at least one stereo camera to at least one construction machine or to a movable carrier, such that the stereo camera can detect at least one detection region within the construction area, preferably a working region of the construction machine, providing at least one reference point, the position of which is known relative to a predefined 3D world coordinate system and which can be recognised in the images of the stereo camera, in the detection region of the at least one stereo camera, calibrating the at least one stereo camera on the basis of the detection of the at least one reference point and triangulation in order to ascertain a transformation between the 3D world coordinate system and a 2D image coordinate system of the at least one stereo camera, preparing a virtual digital 3D terrain model of the construction area by means of digital image processing, in particular stereoscopy, and image recognition on the basis of the detection of the construction area by means of the at least one stereo camera, and representing predetermined working positions and detected actual tool positions and / or actual tool inclinations of the tool of the at least one construction machine in the virtual digital 3D terrain model.

For three-dimensional image capture with the aid of a stereo camera having two cameras, an image of a three-dimensional scene is first captured simultaneously with the two cameras. Characteristic signatures of scene objects within each captured image are determined and assigned to each other in pairs. Characteristic position deviations of the assigned signature pairs from each other are determined. The position deviations are filtered in order to select assigned signature pairs. Based on the selected signature pairs, a triangulation calculation is performed to determine depth data for the respective scene objects. A 3D data map of the captured scene objects within the captured image of the three-dimensional scene is then created. This results in a method for capturing three-dimensional images, which is well adapted for practical use, in particular, for capturing images to safeguard autonomous driving.

To provide a calibration method or the like that can improve the accuracy of identifying a relation among multiple state images based on the multiple state images acquired by a stereo camera at each of multiple different positional attitudes.SOLUTION: A calibration sheet 20 (object) having, on a flat designated surface, designated areas 21, 22, and 23 in which local areas 210, 220, and 230 having three different attributes (RGB values) are arranged so as to be distributed. Three-dimensional positions of respective representative points (centers of gravity) of the designated areas 21, 22, and 23 reflected in each of multiple state images acquired by stereo cameras at different positional attitudes are identified. An affine transformation matrix is obtained so that the three-dimensional position of each representative point in a first state image coordinate system coincides with the three-dimensional position of each representative point in a second state image coordinate system.SELECTED DRAWING: Figure 2

A work information projection system estimates a position in a workplace. The work information projections system includes a camera (13), a stereo camera (14), and a controller. The camera (13) is arranged facing in a first direction and acquires first environment information which is information about an object arranged in and around the first direction. The stereo camera (14) is arranged facing in a second direction and acquires second environment information which is information about an object arranged in and around the second direction. The controller estimates a position in a first coordinate system based on the first environment information when it determines that the second environment information becomes unacquirable.

Systems and methods related to visual guidance for improving autonomous navigation with row following corrections in stereo camera systems are disclosed herein. A visual positioning system may implement a method for navigating a vehicle. The method may comprise: receiving navigation coordinates defining a route comprising a straight path; detecting detected lines that are parallel to the straight path based on images received from at least one camera on the vehicle; accessing ground truth data; deriving vehicle coordinates from the ground truth data; determining a centerline in vehicle coordinates based on the detected lines; determining corrected vehicle coordinates based on the centerline in vehicle coordinates and the vehicle coordinates from the ground truth data; and generating control signals to navigate the vehicle along the route using the corrected vehicle coordinates. The visual positioning system may maintain localization accuracy and provide drift correction in the presence of poor GPS or radio localization.

The invention discloses a robot positioning method based on ultra-wide field angle visual image processing and IMU, and the method comprises the steps: shooting a target image through a binocular stereo camera, converting the target image into a left image and a right image through a depth calculation model with distortion compensation, and extracting feature points in the left image and the right image based on a computer vision technology, solving a depth value of each feature point by using a feature point spatial distribution optimization function, establishing a reprojection residual model taking a frame number as a basic unit for the left and right images through inertial navigation, and obtaining residual terms of the left and right images, and based on the left and right image feature point depth values and the left and right image residual item optimization coupling, realizing a positioning effect on a target image, carrying out visual loopback optimization function detection on the positioning effect, triggering a loopback effect when detecting that the loopback similarity exceeds a threshold value, and carrying out target image positioning again. The method has the beneficial effects that the positioning precision of visual positioning navigation is improved, and accumulated errors of positioning are reduced.

The invention provides a visual identification positioning method, device and equipment for a robot, and the method comprises the steps: collecting a plurality of frames of left and right target images through a stereo camera, carrying out the dual feature detection of the images, extracting point features and line features, and forming complementary feature information; matching optimization processing is carried out on the point-line features, and a high-quality feature matching result is obtained; key frame selection is carried out based on a point-line fusion feature matching result, and redundancy calculation is reduced; and carrying out three-dimensional reconstruction on point-line features in the key frame, and carrying out fusion optimization with inertial measurement unit data to obtain accurate robot position and attitude information. Through a point-line feature fusion mode, the limitation of purely depending on point features in a texture missing environment is effectively solved, the precision and robustness of robot vision positioning are remarkably improved, and the method is suitable for robot autonomous navigation in texture missing and rugged terrain environments.

An image processing device 20 includes a communication unit 21 and a controller 22 (processor). The communication unit 21 acquires a standard image and a reference image captured by a stereo camera 10. The controller 22 calculates a disparity based on the standard image and the reference image. The controller 22 calculates, at each pixel position, a cost value representing a degree of difference for each pixel position between the standard image and each of multiple images obtained by displacing the reference image by multiple different deviation amounts in a direction corresponding to a baseline length direction of the stereo camera 10. The processor aggregates the cost values using dynamic programming and calculates a disparity for each pixel position based on the aggregated cost values for each different deviation amount. The multiple different deviation amounts are discrete values at uneven intervals.

The present disclosure relates to user interfaces for augmented reality experiences including live feeds from one or more external sensors. An electronic device displays a widget dashboard user interface in a three-dimensional environment, displays a representation of a physical tool as guidance for indicating a location of the physical tool relative to a location associated with a video feed, displaying a suggestion for changing the pose of the camera to a predetermined pose based on image data detected when the camera has previously the predetermined pose, displaying a live camera feed and the image data and browsing the image data according to the change in the pose of the camera with respect to the physical object, a live stereo camera feed with a special effect is displayed, input for virtually annotating portions of an object is detected and responsive to, and / or a model of the object is displayed, and input for rotating and / or viewing the model from different depth positions within the model is detected and responsive to.

System and method for a computer vision technique for contactless measurement of vehicle toe are disclosed herein. The method includes capturing with a stereo camera an image containing a vehicle's wheel, segmenting the image, determining a suitable circular component of the wheel and computing the angle of the wheel relative to the camera and, subsequently, to the body of the vehicle. The method includes repeating the process for a plurality of wheels and computing the toe angle of the vehicle based on the obtained results.

An aircraft includes a plurality of stereo cameras. The aircraft further includes one or more processors and one or more memory devices. The one or more memory devices store instructions that are executable by the one or more processors to perform operations including generating a three-dimensional depth map based on a plurality of outputs of the plurality of stereo cameras. The instructions include detecting one or more objects represented in the plurality of outputs. The instructions further include transmitting one or more taxi control signals based on the three-dimensional depth map and the one or more objects.