8677 results about "Field of view" patented technology

The invention discloses an optical lens which is sequentially arranged from an object side to an image side along an optical axis of the lens: a first lens which is a glass lens with negative focal power; the second lens has negative focal power; the third lens is provided with positive focal power; a fourth lens, wherein the fourth lens has positive focal power or negative focal power; an aperture stop; a fifth lens, wherein the fifth lens has a positive focal power or a negative focal power; a sixth lens having a positive focal power or a negative focal power; a seventh lens having a positive focal power or a negative focal power; and the eighth lens is a plastic lens with positive focal power or negative focal power. The lens is formed by mixing glass and plastic, the field angle is larger than or equal to 200 degrees, the aperture is larger than or equal to 1.9, and the lens has the advantages of being large in field of view, large in aperture, high in imaging quality and high in brightness.

The invention relates to the technical field of laser engraving, and discloses a laser engraving method and system capable of automatically correcting coordinates of a galvanometer and a camera, and the method comprises the following steps: calculating a target conversion coefficient based on a calibration size and a pixel size of an image collected by the camera, and controlling the galvanometer to perform laser etching on a cross mark on the surface of a PCB (Printed Circuit Board), recording origin data of a galvanometer coordinate system; adjusting the position of the camera to enable the cross center of the view of the camera to coincide with the cross mark, and calculating the coordinate offset; coordinate space transformation is carried out on all the points to be machined, and galvanometer marking coordinate data are obtained; after laser engraving is carried out on the galvanometer marking coordinate data, an engraving area image is collected, the position residual error and the size proportion deviation are calculated, laser engraving is carried out again, and a laser engraving result is obtained. The technical problem that the visual positioning coordinate and the galvanometer marking coordinate in the laser engraving system are not consistent is effectively solved.

The invention relates to the field of welding, and discloses a non-standard intelligent customized welding system based on vision and surface gradient, which comprises a visual perception module used for iteratively approaching a workpiece from a preset initial height through a self-adaptive high angle shooting exploration mechanism, and combining layered grid division based on a camera view and a progressive multi-angle expansion scanning mode, collecting multi-view three-dimensional point cloud data of the workpiece; and the point cloud processing module is used for performing regional progressive registration on the multi-view three-dimensional point cloud data, implementing threshold constraint based on point cloud curvature characteristics by dynamically adjusting registration step length, and eliminating accumulative errors in combination with pose map optimization. Through self-adaptive high-angle shooting and layered grid scanning, multi-view point cloud can be automatically collected without manually presetting a workpiece model, regional registration and curvature constraint are combined, the workpiece model is constructed, a weld joint structure is automatically extracted based on surface gradient features, traditional manual labeling is replaced, a welding track is generated according to weld joint topology, and the precision is dynamically corrected.

A robot in accordance with at least some embodiments of the present technology includes a neck region through which the robot is configured to transmit and receive light. The robot defines a robot height and includes a body, a head carried by the body, and a neck extending between the head and the body along the robot height. The robot further includes a structural neck frame at a periphery of the neck in a plane perpendicular to the robot height. The structural neck frame defines windows distributed around the periphery of the neck. The robot further includes a sensor disposed at least partially within the structural neck frame. The sensor includes a laser configured to transmit light via the windows and a detector configured to receive light via the windows. A field of view of the sensor extends at least 320 degrees around the neck.

The invention relates to the technical field of unmanned aerial vehicle navigation, and discloses an unmanned aerial vehicle navigation method and system based on computer vision, and the unmanned aerial vehicle navigation method based on computer vision comprises the following steps: collecting a current visual field image of an airborne camera of an unmanned aerial vehicle, and carrying out adaptive image enhancement; performing scene semantic understanding; semantic perception feature extraction is carried out; feature matching and outer point elimination are carried out; floor identification is carried out, and multi-sensor fusion positioning is carried out; plane segmentation, structural constraint extraction and map normalization are carried out; performing visual navigation evaluation, judging a navigation mode according to an evaluation result, and generating an exploration control instruction quantity based on the navigation mode; generating a cross-floor path sequence, optimizing a track in real time, and performing control fusion in combination with a navigation mode identifier and an exploration control vector; according to the method, the navigation problem of the unmanned aerial vehicle in complex scenes such as smoke interference, multi-story buildings and illumination dramatic change in a GPS denial environment is solved, and high-precision autonomous navigation is realized.

The invention provides an automatic operation process management method and device based on multi-sensor fusion, and relates to the technical field of automatic processes, and the method comprises the steps: constructing an instrument pose flow and operation field geometric model under a unified coordinate system through unified timestamp alignment and spatial geometry solution of multi-source sensor data; semantic segmentation and three-dimensional reprojection are combined to generate a shielding probability graph, cross-channel compensation reconstruction is carried out, and the image integrity is improved. And forming a conflict risk set through voxel field discretization and short-time prediction, and performing combined solution with standardized operation process constraints to generate a scheduling instruction and a safety time window. And finally, mapping the image, the pose and the physiological signal to a knowledge graph, and outputting consistency judgment and deviation correction suggestions in combination with a time sequence attention recognition process node. According to the method, the problem that the operation process management is not accurate enough due to the problems of view overlapping and the like of multi-source sensor data can be solved.

The invention relates to the technical field of flight path planning, in particular to an autonomous flight path planning method and system for a road slope inspection unmanned aerial vehicle, and the method comprises the following steps: controlling the unmanned aerial vehicle to fly in a road slope region according to a preset flight path, collecting the aerial image data of the unmanned aerial vehicle, analyzing the aerial inspection adaptive feature value of the unmanned aerial vehicle, and determining the flight path of the unmanned aerial vehicle. Judging whether the feature value is lower than a preset inspection adaptation feature threshold value or not; analyzing a field-of-view missing feature set of the unmanned aerial vehicle based on the aerial image data of the unmanned aerial vehicle if the field-of-view missing feature set is lower than the preset routing inspection adaptive feature value threshold; performing flight path planning processing on the unmanned aerial vehicle based on the field-of-view missing feature set; according to the method, the unmanned aerial vehicle is subjected to flight path planning processing on the basis of the field-of-view missing feature set, so that when an aerial picture is deviated, fuzzy or blind areas, judgment and automatic adjustment are performed in real time, self-adaptive optimization of the flight path is realized, and the road slope inspection efficiency is remarkably improved.

The invention discloses a lightweight display interface rendering optimization system, which relates to the technical field of image processing, and comprises an acquisition module, an interface analysis module, a behavior analysis module and an attention analysis and rendering module, dynamically calculating an effective view radius by utilizing a visual tunneling effect; the interface analysis module performs character string fuzzy matching in combination with the context input by the user, identifies the search intention of the user and improves the weight of a corresponding component; the attention analysis module performs multi-modal weighted fusion on the physiological fixation data and the sparse content saliency thermodynamic diagram; according to the method, by recognizing the semantic intention and the physiological fixation point of the user, on the premise that core visual experience continuity is guaranteed, GPU load and video memory bandwidth occupation are remarkably reduced, and balance of high-performance display and low-power-consumption operation is achieved.

The invention discloses a method for clearly imaging a mask under an optical objective, and relates to the technical field of optical detection and image processing, and the method comprises the following steps: S1, constructing a light intensity distribution model based on the boundary condition of the field of view of the optical objective in combination with the reflection characteristic and incident angle change rule of a metal edge material, and determining the coverage range of metal edge reflection crosstalk, generating a mask boundary interference prediction map; s2, according to the mask boundary interference prediction map, performing region division on the micro-reflectivity image, extracting brightness gradient characteristics of reflectivity lifting in an interference region, and generating a brightness gradient parameter set required by image filtering; the method is based on light intensity modeling, fusion direction filtering, pixel stripping, gradient reconstruction and credibility weighted fusion, realizes closed-loop control from interference prediction to pixel restoration, has high resolution and adaptivity, can accurately strip edge reflection artifacts and restore a real image structure, remarkably reduces misjudgment and rework rate, and is suitable for large-scale popularization and application. And the mask yield and the stability of the detection system are improved.

The invention discloses a three-dimensional modeling method and system, and relates to the technical field of intelligent perception and three-dimensional reconstruction, and the method comprises the steps: taking BIM as a priori, sampling a geometric entity as a visibility evaluation point cloud, and constructing a graph structure environment state under the constraints of a field of view, distance measurement, an incident angle, overlapping and other sensors; on the basis, a deep reinforcement learning agent which is pre-trained by a synthetic scene and subjected to domain randomization migration is introduced, stations and scanning parameters are selected online according to an observation-decision-execution-update closed loop, visibility and coverage are re-estimated after each step of scanning, and self-adaptive correction is carried out on an unexecuted sequence in combination with online optimization; compared with an off-line global optimization method, the method has the advantages that a search space is effectively compressed through candidate station pre-generation and visibility gating, and continuous and adjustable balance is formed among coverage, point cloud quality and operation time by multi-target awards; for engineering constraints such as temporary shielding, site reachability, registration overlapping degree and the like, the strategy can be dynamically replanned in an execution period.

The invention discloses a transformer oil leakage detection method and device based on polarization-ultraviolet fusion imaging, and the device comprises a housing, a support, a camera, an environment induction device, an overall controller, a power supply, a polaroid rotating wheel assembly, a lens seat assembly, and an image processor. And the motor driver, the illumination intensity sensor, the ultraviolet irradiance sensor, the image processor and the power supply are electrically connected with the integral controller respectively. According to the invention, a multi-angle polarization image and a non-polarization image in the same field of view can be acquired, and then polarization characteristics contained in an oil stain fluorescence signal are extracted and effectively distinguished from non-polarization characteristics of background light; in the daytime mode, the transformer oil leakage detection device can identify a target area with relatively high polarization intensity, and through image fusion enhancement processing, non-target background signals are significantly suppressed, and the fluorescence significance of an oil leakage characteristic area is improved.

The invention provides a blood cell image recognition method based on a multi-scale Vision Transform model, and the method comprises the steps: constructing a multi-scale feature extraction architecture, combining the global modeling capability of a Transform network, carrying out the parallel processing of Patches of different sizes, and fusing the multi-scale information, thereby achieving the recognition of a blood cell image. The cells in the blood smear can be comprehensively perceived from microscopic details to macroscopic contexts, so that not only is the adaptability of the model to cell size difference and morphological diversity enhanced, but also the recognition stability under the conditions of cell overlapping and dyeing difference in a complex visual field is improved; the accuracy and calculation efficiency of cell classification and counting are effectively improved, and full-process automation from visual field quality evaluation to automatic cell recognition and counting is achieved.

The invention provides a camera external parameter calibration method and device based on image and point cloud matching, and the technical scheme of the invention is that a point cloud rendering view corresponding to an original point cloud is rotated, so that the point cloud rendering view and a camera image are superposed visually, and initial space association is established; and directly learning and solving accurate camera external parameters from the local relevance between the original point cloud intensity information and the image RGB information in an end-to-end manner by using a deep learning model. According to the scheme, the strict camera-radar orientation consistency requirement in a traditional method is not needed through rough matching, manual participation in the whole process of traditional calibration is replaced, transition from visual alignment to geometric alignment is achieved, and the calibration efficiency and scene adaptability are remarkably improved. Meanwhile, the scheme of the invention initiates a process of visual field cone cutting-perspective projection rasterization-intensity-RGB end-to-end matching, and compared with a traditional feature point method, the calculation complexity is greatly reduced, and the memory occupation is reduced by 80%.

The invention discloses a brain wave monitoring visualization method and system, and the method comprises the following steps: obtaining original brain electrical signals of a user at different time points and task scenes, and carrying out filtering, denoising and segmented cleaning to obtain a preprocessing data set; performing frequency domain analysis on the data set, and extracting waveband power distribution; generating thermodynamic diagram data based on the power value, dynamically superposing the thermodynamic diagram data to the visual field of the user through an augmented reality technology, and displaying the activity intensity of the brain area; and accumulating data for a long time to construct a personalized baseline database, comparing the current power with a scene threshold value in real time, generating warning feedback by associating the thermodynamic diagram when the power is abnormal, and optimizing the baseline database. According to the method, the abstract electroencephalogram signals are converted into the visual thermodynamic diagrams, personalized baselines and dynamic feedback are combined, the problems that traditional monitoring data is difficult to understand, depends on group threshold misjudgment and is lack of dynamic optimization are solved, and the intuition, accuracy and practicability of electroencephalogram monitoring are improved.

A method and system for constructing a three-dimensional (3D) aerial survey of a city street scene include obtaining a plurality of video frames from a calibrated multi-camera setup covering a 360-degree view mounted on a moving vehicle. The plurality of video frames is split into a plurality of 3D parts containing a subset of the plurality of video frames and preprocessing the subset of the plurality of video frames of each part of the plurality of parts to obtain a calculated information. Further, constructing, by the processing circuitry, a 3D representation of each part of the plurality of parts based on the calculated information to obtain a plurality of local 3D reconstructed scene intervals. The method includes stitching and filtering, by the processing circuitry, the plurality of local 3D reconstructed scene intervals to construct the 3D city street scene.

The invention relates to a six-eye camera panoramic video real-time splicing method and system and computer equipment, and the method comprises the steps: synchronously carrying out the image collection through a six-eye camera array, and adding a timestamp to each video frame image; performing real-time feature extraction on the video frame image, and establishing a feature matching relationship in a view field overlapping region of adjacent cameras; based on the feature matching relationship, mapping each video frame image to a unified splicing coordinate system through projection transformation; performing splicing processing on the video frame images after projection transformation through multi-band fusion, and eliminating splicing traces at the boundary of the field of view; and reconstructing the panoramic frame images obtained after splicing processing according to a time sequence, and outputting a continuous panoramic video stream so as to realize real-time and seamless splicing and correction of six paths of high-definition video streams and finally output a global panoramic video stream with no visual fracture and consistent time and space.

The invention discloses a straight gear shape-free measurement method based on single-group line structured light. The method comprises the following steps: constructing an optical platform coordinate system, carrying out line structured light coordinate system calibration through a spherical calibration body, and calibrating the rotation center of a precision turntable; installing a measured straight gear, establishing a straight gear coordinate system, and adjusting the position of the linear structure optical measuring head, so that the measuring field of view of the linear structure optical measuring head covers a root circle to an addendum circle of the straight gear; the straight gear is installed on a precision rotary table, the straight gear is driven to rotate at a constant speed, a linear structure optical probe scans and collects straight gear contour point cloud data and circular grating angle information, and tooth surface three-dimensional point cloud data is obtained; based on the three-dimensional point cloud data of the tooth surface, extracting an addendum circle, a dedendum circle and an involute tooth profile, and calculating spur gear parameters; performing reverse three-dimensional shape modification tooth surface identification on the shape modification straight gear to generate a three-dimensional deviation diagram; and outputting a measurement result and printing a report. The problems of shape-free rapid measurement, modification tooth surface identification and tooth surface three-dimensional deviation characterization of the straight gear with unknown basic parameters are solved.

The invention discloses a reticulocyte recognition and grading system based on a blood smear, and particularly relates to the field of medical cell morphology examination, and the system comprises an image acquisition module, a staining normalization module, an instance segmentation module, an erythrocyte classification module, a reticulocyte grading module and a statistics output module. The image acquisition module adopts an automatic microscope platform to continuously scan the blood smear under a 100-time visual field, acquires a high-quality bright field channel image through an automatic focusing technology, and monitors image definition, contrast and illumination uniformity; the statistical output module is used for calculating the proportion and bluish violet intensity statistics of reticulocytes of each level, and generating a visual quality control result and a diagnostic report; according to the invention, full-automatic processing from samples to reports is realized, interpretability and high classification precision are both considered, subjective difference and omission ratio of manual microscopic examination are significantly reduced, and efficiency and consistency of clinical detection are improved.

The invention relates to the technical field of robots, in particular to an instrument monitoring method, system and device for an inspection robot and a medium, the method is used for searching an instrument to be inspected by using the inspection robot and monitoring the instrument to be inspected, and the method comprises the following steps: obtaining a view scene image collected by the inspection robot, performing image segmentation and feature extraction on the view scene image; obtaining the exploration value of the instrument area; obtaining candidate paths from the inspection robot to the instrument areas; evaluating a cost function of each candidate path; carrying out adaptive visual angle adjustment and data acquisition on the inspection instrument; the monitoring method is an exploration type sensing strategy based on exploration value driving, and an instrument target can be found in the environment. And in combination with a historical task map, instrument semantic priori and current perception data, the information value of the candidate region is evaluated, and optimal decision making is performed on the path by fusing environmental factors such as illumination, shielding and equipment states, so that priority selection and dynamic reconstruction of the target region are realized.

The invention provides an indoor SLAM map construction method and system, and relates to the technical field of image processing, and the construction method comprises the steps: building a unified global space reference through cross-device space-time calibration, supplementing the visual blind area information of a robot in real time through the global static features extracted by an environment camera, and obtaining the visual blind area information of the robot; and meanwhile, dynamic interference features are accurately eliminated in combination with continuous frame analysis, and finally, the pose of the robot is continuously corrected by taking global features as anchor point constraints in back-end optimization. The complete technology chain enables the constructed indoor three-dimensional map to have higher integrity, precision and consistency, significantly improves the positioning robustness and navigation reliability of the robot in an environment with dense goods shelves and dynamic activities, reduces the performance dependence on a robot body sensor and the scene reconstruction cost, and improves the reliability of the robot. And a stable and efficient environment sensing basis is provided for automatic operation of industries such as storage and archive management.

The invention discloses a single view reconstruction and rendering method, which belongs to the field of view reconstruction and rendering, and comprises the following steps of: firstly, generating multi-view feature representation with strong geometric consistency from a single input image by introducing an image diffusion module of a cross attention mechanism; a point cloud reconstruction module with self-attention and cross-attention is utilized, and multi-view information is fused to reconstruct an accurate three-dimensional point cloud; and finally, constructing differentiable three-dimensional Gaussian representation based on the point cloud, rendering the differentiable three-dimensional Gaussian representation, and outputting a new view angle image, a normal map and a depth map. According to the system, a staged training strategy is adopted, and a composite loss function including multi-scale bidirectional consistency smooth loss and feature consistency loss is innovatively used for optimization. According to the method, the problems of low geometric accuracy, multi-view inconsistency, detail missing and the like in single-view reconstruction are effectively solved, and the method can be widely applied to the fields of virtual reality, digital twinning, cultural heritage digitization and the like.

A viewpoint setting unit of an image data generation device sets a reference viewpoint on a basis of position and orientation information regarding a head-mounted display, and a reference image drawing unit generates a reference image in a field of view corresponding to the reference viewpoint. An additional data generation unit acquires color information regarding an occluded part not represented in the reference image from a different viewpoint as additional sampling data. A reprojection unit of the head-mounted display transforms the reference image into an image from a latest viewpoint and determines a pixel value of the hidden part using the additional sampling data.

A vehicular camera monitoring system includes an electronic control unit (ECU) at a vehicle and a support arm movably disposed at a side portion of the vehicle, with the support arm having a base end attached at the side portion of the vehicle and a distal end opposite the base end. A camera is disposed at the distal end of the support arm. The support arm is movable between a stowed position and an extended position. A cover element covers an aperture at the side portion at least when the support arm is in the extended position. The camera, when the support arm is in the extended position, captures image data and provides captured image data to the ECU, which processes the provided image data for (i) display of video images derived from provided image data and / or (ii) detection of an object in the field of view of the camera.

The invention relates to the technical field of monitoring light supplement adjustment, and discloses a monitoring light supplement automatic adjustment system based on ambient light detection. An ambient light dynamic sensing module of the system captures visible light and infrared spectrum components of a monitoring area in real time through a multispectral sensor array, constructs a light intensity distribution model in combination with illumination intensity historical data, and outputs a theoretical illumination distribution diagram; the spectral feature analysis module compares the theoretical distribution map with the actually measured light field data in a multi-dimensional manner, performs spectral deviation detection and generates a spectral difference feature tensor; the light supplement demand mapping module inputs the tensor into a space illumination analysis network, and generates a light supplement coverage demand thermodynamic diagram and calibrates the boundary of a low-illumination area in combination with a field angle of monitoring equipment and position coordinates of a light supplement lamp; and the self-adaptive light supplement strategy execution module starts a multi-band mixed light supplement mode for a high-demand area according to the thermodynamic diagram, and performs phase cooperative control on adjacent light supplement lamp groups. The system realizes dynamic and accurate adjustment of light supplement, and can effectively adapt to complex ambient light changes.

The invention discloses a thoracoscope minimally invasive cardiac surgery navigation system based on multi-modal image fusion, and the system comprises the steps: constructing a 5D heart digital twin containing an anatomical structure, a soft tissue boundary, metabolic activity and electrophysiological information through fusing preoperative CT, MRI, PET and intraoperative ultrasonic images; real-time dynamic registration is realized by using an electrocardio gating driven biomechanical model; superposing the multi-color coding navigation information to the visual field of the thoracoscope through a wavelength selection type spectroscope; a dynamic risk scoring model is constructed based on the distance, the speed and the tissue vulnerability, and three-level grading intervention is triggered; a miniature force feedback actuator is integrated to realize closed-loop control; and pre-operation virtual drilling and post-operation federal learning optimization are supported. The system remarkably improves the surgical precision and safety, and is suitable for high-difficulty heart minimally invasive surgeries such as mitral valve repair and atrial fibrillation ablation.

The invention discloses a retina thickness prediction method and system based on a multi-modal image, and the method and system achieve the effective estimation of the retina thickness under a low-cost condition through feature alignment and fusion modeling, and improve the basic screening and follow-up visit capability. According to the invention, through fusion of the multi-mode retina image data, the structure and function information of the optic nerve can be more comprehensively obtained, and the prediction accuracy of the thickness of the retina nerve fiber layer (RNFL) is improved. The OCT high-resolution hierarchical structure and the wide-view texture features of the eye fundus image are combined, so that anatomy and pathological states of optic nerves can be truly restored. The method can be used as an auxiliary method for early screening and early warning of optic neurodegenerative diseases such as glaucoma, and provides support for low-cost and high-efficiency primary screening and clinical auxiliary decision making.

The invention discloses a defect multi-angle detection and fusion method based on a vector graph and affine transformation, and relates to the technical field of image processing, and the method comprises the steps: collecting a plurality of sub-images with overlapping regions at a single angle; constructing a collision map at the angle, wherein the view field of each grid corresponds to a sub-image; extracting defect contours from the sub-images and converting the defect contours into defect vector graphs; according to the defect vector set of all the sub-images at the angle, collision detection and cross-sub-image defect fusion are carried out based on the collision map at the angle, and a defect set at the angle is obtained; one angle is selected as a reference angle, other angles are selected as target angles, a defect set of the target angles is transformed to a reference angle coordinate system based on affine transformation, collision detection and cross-angle fusion are carried out on the transformed defect set and the defect set of the reference angles, and a final optical assembly defect set is obtained. And integrated detection of large-area coverage, high-precision alignment and high-efficiency fusion is realized.

The invention discloses an automatic cattle checking method and system based on two-dimensional panoramic vision, and belongs to the technical field of computer vision and intelligent breeding, and the method comprises the following steps: reasonably arranging a plurality of fixed cameras in a cattle farm area, obtaining the internal reference and distortion coefficient of each camera through employing a camera calibration technology, and obtaining the internal reference and distortion coefficient of each camera; performing real-time distortion correction on the collected video frames; on the basis of side-by-side splicing or homography matrix perspective transformation, all paths of corrected images are fused into a complete two-dimensional panoramic image, and a view blind area of a single camera is eliminated; calling a lightweight target detection model on the panorama, and extracting bounding boxes and confidence coefficients of all cattle at one time; sorting according to the confidence from high to low, performing IOU non-maximum suppression de-duplication on the detection frame, and ensuring that the same cattle only counts once in an overlapping region; and the whole process is completed through the edge computing node. According to the invention, efficient, real-time and accurate on-site cattle checking of a large-scale cattle farm can be realized.

An x-ray apparatus and method can improve x-ray imaging in a variety of ways. For example, the improve x-ray apparatus can reduce scatter from x-ray images acquired by two-dimensional detectors. An improved 2D x-ray apparatus can provide 3D imaging for medical and / or industrial applications. An improved 2D x-ray apparatus and method can produce separate material imaging, and composition analysis for characterization and correlation of image, densitometry, and composition information of individual component or individual material within a single subject. Non-rotational 3D microscopy, combining 2D or 3D full field x-ray imaging and high resolution 2D or 3D x-ray microscopy or spectral absorptiometry and spectroscopy can achieve a higher resolution and wider field of view in x-ray imaging and quantitative analysis in 3D and real time. The x-ray apparatus can improve tracking and / or surgical guidance in time and / or space.

The invention provides an optical lens, which comprises four lenses with focal power and sequentially comprises a first lens with negative focal power, a second lens with negative focal power, a third lens with positive focal power, a fourth lens with negative focal power, a fifth lens with negative focal power and a sixth lens with negative focal power from an object side to an imaging surface along an optical axis, the object side surface of the second lens is a convex surface, and the image side surface of the second lens is a concave surface; the object side surface of the third lens is a convex surface, and the image side surface of the third lens is a convex surface; the image side surface of the fourth lens is a convex surface; wherein the maximum field angle FOV of the optical lens and the real image height IH corresponding to the maximum field angle of the optical lens meet the following conditions: 35 degrees / mmlt; fOV / IHlt; 46 degrees / mm; the focal length f3 of the third lens and the focal length f4 of the fourth lens satisfy 0.5 lt; f3 / f4lt; and 0.8. According to the optical lens provided by the invention, through specific surface shape matching and reasonable focal power distribution, the lens has one or more advantages of an ultra-wide angle, a large aperture, high imaging quality, high collimation and the like.