131 results about "Eye detection" patented technology

The embodiment of the present invention discloses a method for predicting corneal reshaping parameters based on an artificial neural network, and relates to the technical field of orthokeratology lenses. The method comprises: obtaining an initial sample data set, deleting target samples that do not contain necessary parameters, and obtaining a basic sample data set; preprocessing the basic sample data set to obtain a final sample data set; training the initial artificial neural network model to obtain a preliminary model; using the preliminary model to forward propagate the input layer data of the basic sample data set to obtain a calculation result and compare it with the result of the basic sample to obtain a final sample data set, and using the final sample data set to train the preliminary model to obtain a prediction model; inputting actual eye detection data into the prediction model to obtain corresponding corneal reshaping parameters. The present invention splits the data to be predicted into multiple dimensions, constructs different prediction models according to each data to be predicted, and then performs distributed training and uses them in combination.

The invention belongs to the technical field of eye detection, and particularly relates to a myopia progress risk prediction system, which comprises a data acquisition module used for collecting a plurality of biological index data related to myopia progress, including but not limited to ocular axis length, corneal curvature, diopter, age, gender, lifestyle, genetic information and the like; the multi-factor analysis module is used for comprehensively analyzing multiple pieces of biological index data and modeling the individualized myopia progress risk based on a multi-factor interaction relationship; the regression algorithm module is used for collecting multiple pieces of biological index data; by analyzing multiple biological indexes at the same time, comprehensive evaluation of the myopia progress risk is achieved, compared with a traditional method which only depends on a single index for prediction, the system considers interaction of multiple factors, individual differences and environmental influences can be captured more comprehensively, and therefore prediction accuracy and reliability are remarkably improved.

The invention provides an inflatable package air tightness detection device and detection method, and relates to the technical field of package detection. A top cover is arranged at the top of the detection box, a pressure sensor is arranged at the bottom of the top cover, a negative pressure pipe is arranged on the detection box and communicated with a negative pressure system, an outer cover is arranged in the detection box and connected with the top cover, a plurality of detection covers are connected to the inner side of the outer cover, and the detection covers are sequentially and tightly connected into a whole. All the detection covers are connected to form an enclosed shape which is matched with the side part and the top of the detected inflatable package, the detection covers and the top of the outer cover are communicated with a detection pipe, the top end of the detection pipe is open, the detection pipe is provided with a detection sleeve, and the detection sleeve is provided with a photoelectric detection assembly. According to the invention, whether bubbles pass through an optical signal path or not is detected through photoelectric sensing, manual eye detection is replaced, the bubble detection accuracy is improved, and detection errors are avoided.

The invention relates to the technical field of unmanned aerial vehicle detection, in particular to a civil small unmanned aerial vehicle cat eye detection and countering system which comprises the steps that a cat eye detection module collects cat eye reflection characteristic signals, environment sensing data and unmanned aerial vehicle flight state associated information in an airspace; the threat level evaluation center identifies the type of the unmanned aerial vehicle and the intrusion risk level through an improved random forest model, and measures the real-time airspace position; the dynamic trajectory modeling module constructs a digital twin flight model of the civil small unmanned aerial vehicle, and simulates a flight trajectory and a potential intrusion path by using an intention pre-judgment algorithm; the grading countering unit generates a non-destructive countering strategy according to the intrusion risk grade, the flight path and the potential intrusion path; the man-machine interaction unit constructs a visual airspace monitoring scene, renders a detection result, an intrusion risk level and a countering effect in real time, and carries out man-machine interaction operation. Therefore, the problems of insufficient perception, poor decision collaboration and the like in the prior art are solved.

A method of a biometric recognition system of performing real-eye detection, and a biometric recognition system performing the method. In an aspect, a method of a biometric recognition system of performing real-eye detection is provided. The method comprises capturing a plurality of images comprising a representation of an eye of the individual, which images are captured utilizing polarized light reflected at the eye and received at a polarization-sensitive camera capturing said images, wherein for each image being captured a different polarization rotation is selected, detecting, from the representation in each captured image, birefringent features of a cornea of the individual, and determining, by matching the detected birefringent cornea features of the captured images with the expected birefringent cornea features, whether the detected birefringent cornea features are correctly rendered in at least one of the captured images; and if so determining that the eye is a real eye.

The invention discloses a lightweight sight line estimation method based on global information fusion, relates to the technical field of computer vision and intelligent driving, and solves the technical problems that an existing sight line estimation model is large in parameter quantity, is not adaptive to a vehicle-mounted multi-mode scene and is insufficient in robustness under a complex working condition. The method comprises the following steps: firstly, acquiring a driver image, an external scene image and vehicle running state data, and acquiring a target image through face and eye detection; based on a global information fusion module fusing CNN and Transform and a Res CBAM module, multi-modal global information features of vehicle state and driving behavior priori are obtained; deep modulation fusion of the local visual features and the global information features is completed through a double-stage fusion module, and finally the sight direction or the gazing area of the driver is output. The method realizes the unification of light weight and high precision of the model, is adaptive to vehicle-mounted complex working conditions, has both robustness and real-time performance, and can be widely applied to a vehicle-mounted driver monitoring system.

A method of a biometric recognition system of performing real-eye detection and associated biometric recognition system are disclosed. The method comprises capturing at least one image comprising a representation of an eye of the individual, which image is captured utilizing polarized light reflected at the eye and received at a polarization-sensitive camera capturing said image, wherein a polarization configuration is selected which produces an iso-chrome pattern of the representation of the eye in the captured image, detecting, from the representation, birefringent features of a cornea of the individual, aligning the detected birefringent cornea features with birefringent cornea features of an expected eye representation, determining, by matching the detected birefringent cornea features with the expected birefringent cornea features, whether the birefringent features are correctly rendered in the captured image, and if so determining that the eye is a real eye.

The invention is related a method and a remote eye tracking system for determining a position of at least one eye of a subject. The method comprises the steps of: illuminating a face of a subject using at least one infrared (IR) illuminator off-axis from at least one image sensor; capturing at least one image of the face using the at least one image sensor at a time instant; and using a processing circuitry of the remote eye tracking system, performing processing steps of: determining at least one pupil candidate associated with the at least one image; determining at least one glint candidate associated with the at least one image; determining at least one pupil-glint candidate group, comprising at least one pupil candidate and at least one corresponding glint candidate; generating a score value for each of the at least one pupil-glint candidate groups; and determining an eye position of at least one eye of the subject in the at least one image based on the pupil-glint candidate group with the highest score value.

The invention provides an eye detection device, and belongs to the field of wearable medical supplies. The device comprises a pair of glasses, and an acquisition module and a light source module which are arranged on the glasses, the acquisition module is used for acquiring images and optical signals; the light source module is used for illumination. According to the invention, illumination required by eye test can be provided, and the eyes of a subject can be detected; through the VR, AR or XR technology, rich and diversified images can be provided for the subject for eye detection and training.

The invention relates to a detection device for detecting the printing quality of contact lenses, and belongs to the technical field of detection devices.The detection device comprises a detection table and a visual detection assembly, a support is arranged on the detection table, the visual detection assembly is fixedly arranged on the support, a bearing disc is arranged below the visual detection assembly, and a plurality of containing grooves are formed in the bearing disc; a rotating assembly for driving the bearing disc to rotate is arranged on the detection table, a material placing plate and a material taking plate are arranged on the two opposite sides of the bearing disc correspondingly, fixing rods are fixedly arranged on the lower surfaces of the material placing plate and the material taking plate correspondingly, and the ends, away from the material placing plate or the material taking plate, of the fixing rods are fixedly connected with the upper surface of the detection table; a first placing assembly capable of placing the contact lenses on the material taking plate on the bearing disc is arranged between the material placing plate and the bearing disc, and a second placing assembly capable of placing the contact lenses on the bearing disc on the material taking plate is arranged between the material taking plate and the bearing disc.

The invention relates to an intracranial pressure detection system, method and device, a controller and a storage medium, and belongs to the field of medical detection.The system comprises an image acquisition device, a display device and the controller; wherein the controller is electrically connected with the image acquisition device and the display device respectively; the controller is configured to respond to an eye sampling image about a detection object output by the image acquisition device; identifying eye features reflecting the intracranial pressure of the detection object in the eye sampling image through a preset eye detection model; determining an intracranial pressure level numerical value of the detected object according to the eye features and a preset mapping relation; wherein the mapping relation reflects that different eye features correspond to different intracranial pressure level numerical values; and outputting the eye sampling image and the intracranial pressure level value to the display device.

This invention relates to a method for ultra-high sensitivity and specific naked-eye detection of trace aromatic compounds. The method utilizes the long afterglow induced by the specific interaction between the analyte and a matrix as the output signal to achieve naked-eye detection of the analyte. The aromatic compounds are aromatic pollutants and aromatic organic metabolites. This invention utilizes the organic long afterglow induced by mixing the analyte G with the host molecule H through methods such as heating and melting, solvent evaporation and crystallization, matrix adsorption, and paper chromatography as a monitoring signal to achieve ultra-high sensitivity and specific naked-eye detection of trace aromatic compounds. The afterglow induced by the analyte G is highly dependent on the type and content of the analyte and matrix, which gives this detection method extremely high sensitivity and selectivity. The method is simple to operate, rapid, visible to the naked eye, requires inexpensive and readily available materials, and provides stable results.

The utility model discloses a display device of eye detection equipment and the eye detection equipment. The display device is formed by sequentially overlapping a PCB lamp panel, a light guide cover, a transparent acrylic plate, a film and a semi-transparent black acrylic plate. According to the display device, a plurality of lamp beads are distributed on a PCB lamp panel according to test requirements, gradient color balls are printed at the positions, corresponding to the lamp beads, in a light-transmitting area of a film, light emitted by the lamp beads is guided by a light guide cover, dodging is conducted through a dodging film, then the light is projected to the film through a transparent acrylic plate, and the light is emitted out of the light-transmitting area of the film. Compared with the prior art, the display device provided by the utility model has the advantages of simple structure and low cost while providing a good visual identification pattern for a testee, and the display device can be applied to the field of eye detection equipment, so that the visual identification rate can be increased, and the display device can be widely applied to the field of eye detection equipment. The cost of main body hardware configuration of the eye detection equipment can be reduced.

An Artificial Intelligence Gaze Interface Sensor (AI GIS) system and method for precisely tracking human gaze on a digital or projected view plane without head-mounted hardware. A context camera detects a user's face and matches it against stored biometric profiles using AI facial recognition, automatically loading personalized eye geometry, inter-pupillary distance and gaze calibration data. A conditional activation controller initializes a second Peregrine Foveal Camera (PFC), modeled after the dual-fovea retina of the Falco peregrinus, only upon confirmed eye detection. An AI algorithm triggers visual effects, hidden content, animations, gaze-based engagements and semantically mapped audio on the digital or projected plane based on gaze coordinate outputs, from a dedicated computational pipeline, correlated to the digital or projected plane. This invention serves as the sensing layer for U.S. application Ser. No. 18 / 395,290.

The embodiment of the invention discloses a sound prompting method and device for fatigue of a driver of an environmental sanitation vehicle. A specific embodiment of the method comprises the following steps: acquiring a driver face image sequence and a vehicle control information sequence; performing eye detection on each driver face image in the driver face image sequence to obtain eye detection information; in response to the fact that the eye detection information meets a preset driver fatigue condition, generating a driver fatigue level identifier based on the vehicle control information sequence and the eye detection information; based on the driver fatigue level identifier, generating a corresponding driver fatigue prompt tone, and sending the fatigue prompt tone to an audio device for sound prompt, the driver fatigue prompt tone being a question prompt tone sent to the driver. According to the implementation mode, fatigue sound prompting can be more accurately carried out on the driver, and it is ensured that the sent prompting sound can achieve the sound prompting purpose.

The invention relates to a binocular vision distance measurement method based on a multi-eye micro-super lens. The method comprises the following steps that a measured object, a telescope structure, the multi-eye micro-super lens and an optical detector are sequentially arranged in the light path direction; acquiring a multi-view detection image of the detected object at different set positions as a calibration image set; a pair of sub-eyes of the multi-eye micro-super lens is selected to form a binocular ranging structure; fitting a function relationship between the distance from the measured object to the telescope structure and the imaging parallax value of the binocular ranging structure based on the calibration image set; and acquiring a multi-view detection image of a detected object at an unknown position, analyzing to obtain an imaging parallax value of the binocular ranging structure, and substituting the imaging parallax value into the function relation to calculate to obtain a distance prediction value from the current position of the detected object to the telescope structure. According to the invention, the sub-eye pairs of the multi-eye micro super lens are adopted to replace a traditional binocular vision device and are optimized, so that the calibration process is simplified while the measurement precision is ensured, and the limitation on the physical structure of the traditional binocular vision is broken through.

1. Name of the designed product: visual quality analyzer. 2. Use of the designed product: for eye detection. 3. Design points of the designed product: in shape. 4. Picture or photo best indicating the design points: perspective view 1.

1. The name of this design product: Visual Quality Analyzer. 2. Purpose of this design product: for eye detection. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.

Systems and methods of detecting pupillary positions on a head of a subject are described. While a camera and a light source are positioned in front of the head of the subject, the camera is caused to capture image data representative of a frontal portion of the head of the subject. From the image data, a face of the subject is detected. Up to two eyes are identified from the detected face. A reflection of the light source on each identified eye is detected. A pupillary position of each identified eye is estimated based on a position of the detected light source reflection on the identified eye. One or more of interpupillary distance, left pupil distance, and right pupil distance may be determined from the estimated pupillary positions.

This invention relates to the field of power line inspection equipment technology, and discloses a power line insulator defect detection device based on binocular UAV ensemble, comprising: a UAV ensemble execution module, a binocular vision inspection module, an ensemble collaborative control module, a data processing and defect identification module, a wireless communication module, and a ground monitoring terminal; the UAV ensemble execution module adopts a master-slave ensemble architecture, consisting of one master-controlled UAV and several slave-controlled inspection UAVs forming an inspection ensemble. By employing binocular synchronous imaging technology, it simultaneously acquires two-dimensional appearance and three-dimensional depth information of the insulator, completely solving the problems of single-eye detection lacking depth and prone to false detection and missed detection; moreover, the master-slave ensemble architecture enables multi-machine synchronous collaborative operation, with a wide coverage area, high inspection efficiency, and the ability to complete long-distance line inspections in one go, possessing fault redundancy capability, and significantly improving operational stability and continuity.

The invention discloses an eye movement detection assembly and a head-mounted display device, and belongs to the technical field of electronics. The eye movement detection assembly comprises a first eye detection assembly, a second eye detection assembly and a driver. The first eye detection assembly comprises a first camera and a first LED lamp group, a first signal end of the first camera is electrically connected with an enabling end of the driver, and a first driving end of the driver is electrically connected with the first LED lamp group; the second eye detection assembly comprises a second camera and a second LED lamp set, the first signal end of the second camera is electrically connected with the enabling end of the driver, and the second driving end of the driver is electrically connected with the second LED lamp set. The head-mounted display device comprises the eye movement detection assembly.

The application discloses an ASD child gaze detection method and device, and a hand-eye coordination ability test equipment and method. The gaze detection method comprises the following steps: constructing and training a gaze detection model; collecting video data containing the face of an ASD child and inputting the video data into the trained gaze detection model to determine whether the ASD child gazes at a target; the gaze detection model comprises a spatial feature extraction module, which extracts spatial features of the video data frame by frame and outputs low-level detail features and high-level semantic features; a time feature enhancement module, which enhances the time features of the low-level detail features and the high-level semantic features output by each frame; and a gaze detection result generation module, which uses an SSD detection framework to output an eye detection frame of a current frame, and then uses a memory enhancement process to gather key information from long-term frames and short-term frames to enhance the eye detection frame of the current frame, so as to obtain the position of the eye detection frame of the current frame and a gaze contact classification result. In the test of the application, the tester does not need to wear and participate in calibration of any equipment.

The utility model discloses a multistage optical eye detection circuit with carrier control, comprising a chip U1 used for generating carrier signals with fixed frequency and duty ratio; the pre-stage carrier amplification circuit module is connected with the chip U1 and is used for amplifying a driving carrier signal; the multi-stage infrared emission circuit module is connected with the pre-stage carrier amplification circuit module and is used for simultaneously transmitting the amplified carrier signals in the form of electromagnetic waves through multi-path cascaded infrared emission tubes; and the multi-stage infrared receiving circuit is connected with the chip U1 and is used for receiving infrared signals. According to the utility model, the purpose of detecting the position and the motion state of an object is achieved through the sending and receiving mechanisms of the multi-stage infrared signals, and meanwhile, the circuit is simple to realize and high in stability.

The utility model relates to the technical field of warp knitting machines, and discloses a defective cloth detection device of a warp knitting machine, which comprises a laser broken yarn monitoring device controlled by a warp knitting machine control cabinet and a light auxiliary device for assisting artificial eye detection, the light auxiliary device comprises a strip-shaped lamp and a lampshade, the strip-shaped lamp is fixedly connected with the lampshade, and the light auxiliary device is connected with the warp knitting machine control cabinet. The lampshade is fixed with the warp knitting machine box body; the lampshade comprises an inclined upper plate, a long-strip-shaped lamp fixing side plate and a horizontal lower plate. The lampshade is of an integrated bent structure. And the inclination angle of the inclined upper plate is 40-60 degrees. The laser broken yarn monitoring device is arranged below the horizontal lower plate and fixed to the warp knitting machine rack. According to the utility model, through combination of automatic laser broken yarn monitoring and artificial eye detection secrecy, the photo-assisted device for assisting artificial eye detection is simple in structure, low in cost and very good in use effect, and the combination of the two can effectively improve the weaving quality, so that the production cost is reduced.

The embodiment of the application provides a defect detection method, device and electronic equipment. In the embodiment, an AI algorithm is used for preliminary positioning of defects in a glove image, initial classification is performed on a suspected defect area, a suspected defect category is obtained, fine classification is performed on the suspected defect area, a target defect category is obtained, automatic detection of the production quality of the glove is realized through machine vision, manual naked-eye detection is replaced, detection efficiency is improved, and the situation of missed detection is avoided. Further, the AI algorithm and the traditional 2D algorithm (i.e., the fine classification process described above) are combined to realize defect detection of the glove, the advantages of the AI algorithm and the traditional 2D algorithm are fully utilized, and the defect detection efficiency and accuracy of the glove are improved.

The invention is suitable for the technical field of naked eye 3D display and the technical field of image processing, and provides a camera-based display terminal system and a control method, and the camera-based display terminal system comprises a camera which is used for obtaining an eye image of a user, carrying out the eye detection of the eye image of the user, obtaining the eye position of the user, and outputting the eye position of the user; transmitting the user eye position to a processing unit; the network connection module is used for acquiring current time and transmitting the current time to the processing unit; the processing unit is used for receiving the eye position of the user and the current time, obtaining three-dimensional image content corresponding to the application mode when the current time is preset time, rendering the three-dimensional image content to obtain original left and right views, and adjusting the original left and right views according to the eye position of the user to obtain left and right views conforming to the visual angle of the user; and the naked-eye 3D display screen is used for displaying left and right views conforming to the visual angle of the user. According to the invention, the application range of the naked-eye 3D display screen is widened.

The invention relates to a driver monitoring system test evaluation method based on a simulation robot. Comprising the following steps: step 1, constructing a simulation robot for a DMS test; 2, designing a DMS test simulation robot control system; step 3, establishing a DMS system; step 4, generating and evaluating a test case; according to the method, firstly, a simulation robot used for DMS testing is constructed, then a steering engine is selected and arranged, and fine control over fatigue actions of the simulation robot is achieved through control of a microcontroller; a python language is used as a development basis, modular design is adopted, eye detection, head posture estimation, attention evaluation, parameter configuration, a camera interface and the like are included, and a detected DMS system is deployed; and finally, based on the national standard and the actual driving behavior, generating an efficient and high-coverage test case set by adopting a combined test theory, and executing through a control system, so that the problems of low efficiency, high cost, uncontrollable action, insufficient scene coverage, lack of a standardized evaluation system and the like of the existing DMS test method are solved.

The application relates to the field of eye detection, and discloses a three-dimensional model construction method based on ophthalmic detection. First, human eye state information is collected, and the human eye state information is pretreated to obtain initial eye state information; data analysis is performed on the initial eye state information to establish initial parameters of an eye three-dimensional model; parameter optimization is performed to obtain screening parameters of the eye three-dimensional model; the eye three-dimensional model is established, eye key points in the eye three-dimensional model are collected, and eye screening point data are bound for the eye key points; the eye key points are normalized, screening operation is performed through big data comparison, and final eye state information is obtained; geometric structure reconstruction is performed to obtain a reconstructed eye three-dimensional model; the application solves the problems that the prior art eye detection is inaccurate, is easy to affect a diagnosis result, and the existing eye model has a large difference in size, position and shape from actual patient eyes.

The invention belongs to the technical field of eye detection, and provides an eye position image acquisition and management method and system. The method comprises the following steps: grouping eyeball rotation images according to eyeball directions; predicting a first key parameter based on the illness state record data of the user and each historical eyeball rotation image corresponding to any orientation, and extracting a second key parameter from each eyeball rotation image grouped in the same orientation; target eyeball rotation images are screened from the groups, third key parameters of eyeballs are extracted from the target eyeball rotation images, all the target eyeball rotation images are synthesized into a panoramic image according to the directions corresponding to the groups to which the target eyeball rotation images belong, and the panoramic image and the third key parameters are stored in an associated mode. According to the method, the eye position image of the user and the corresponding eye feature parameters can be automatically collected, the data stored in an associated mode can be conveniently subjected to analysis such as current strabismus detection and screening and subsequent contrastive analysis of the recovery degree, and the strabismus condition analysis efficiency can be remarkably improved.