106 results about "Eye state" patented technology

The invention provides a classroom student concentration degree monitoring system and method based on computer vision. The system comprises a vision collection module, an edge calculation unit and a cloud analysis platform. A multi-dimensional sensing mode combining head posture analysis, eye state tracking, facial expression recognition and body movement detection is adopted to evaluate the concentration degree, through a dynamic feature fusion mechanism, the system can intelligently adjust the weight ratio of different modal features, the limitation of single-dimensional analysis in a traditional method is effectively solved, and the accuracy of the system is improved. The system adopts edge calculation and cloud analysis, ensures high efficiency of data processing, ensures reliability of complex algorithm operation, and has important value for improving classroom teaching quality and learning efficiency. According to the invention, through multi-modal visual analysis, behavior characteristics and physiological reactions of students in class are monitored in real time, the concentration level of the students is comprehensively evaluated, and objective teaching feedback and improvement basis are provided for teachers.

The invention discloses an optical adjustment method, head-mounted display equipment and a computer readable storage medium, and relates to the technical field of head-mounted display equipment. The optical adjustment method is applied to the head-mounted display device, the head-mounted display device comprises a variable-focus lens, and the method comprises the following steps: acquiring eye state change data of a wearer; according to the eye state change data, through a pre-trained optical parameter prediction model, a target optical parameter is obtained through prediction, and the target optical parameter comprises a target curvature radius; and based on the target curvature radius, performing curvature adjustment on the variable-focus lens. According to the invention, the focusing state of the optical system can be adjusted in a more accurate matching manner, so that the VAC effect of the head-mounted display device is reduced.

The invention discloses a control method and device for a head-up display device in a vehicle, the vehicle and a readable storage medium. The method comprises the steps that current eyeball state information of eyeballs of a driver driving the vehicle is collected; determining current focusing state information of eyeballs based on the current eyeball state information; determining projection parameters of the head-up display device based on the current focusing state information; and controlling the head-up display device based on the projection parameters. According to the method, the projection effect of the head-up display device in the vehicle is improved.

The invention relates to the technical field of machine learning, in particular to the field of machine learning supporting a neural network model, and provides an eye movement detection method and device in an eye-closed state, which are used for identifying an image in the eye-closed state and obtaining a real-time movement condition of an eyeball by constructing a deep learning neural network model. The detection result of the continuous frame is associated with a tracker, a motion track is calculated according to the position change of the target in the continuous frame, and the track is represented by a series of coordinate points and can be further converted into motion parameters such as distance, speed and acceleration; and a detection frame is arranged, and a tracking trajectory and motion parameters are displayed on a video picture in real time, so that a user can conveniently observe and analyze a result.

The invention relates to the field of optical lenses, in particular to an optical lens design and manufacturing method, which comprises the following steps of: determining respective characteristic quantities of a central region and a microstructure region in an optical lens according to an actual eye state of a target object; according to the boundary and the characteristic quantity of the microstructure area, determining an initial microstructure layout of the front and rear surfaces of the microstructure area so as to determine an out-of-focus change characteristic of the optical lens, thereby correcting the initial microstructure layout into a final microstructure layout; according to the final microstructure layout, constructing respective three-dimensional curved surface models of the front surface and the rear surface of the microstructure area; and according to the three-dimensional curved surface model, the front surface and the rear surface of the microstructure area are machined. The front surface and the rear surface of the optical lens are matched and designed with proper microstructures, so that the optical lens is ensured to increase higher diopter in the whole microstructure area, and defocus stimulation with enough strength is provided.

The application discloses an eye state detection device and a detection method. The device comprises a support frame, the back of the support frame is provided with a bandage, the front side of the support frame is provided with a lens frame, the front side of the support frame is provided with a driving assembly for driving the horizontal movement of the lens frame, the inside of the lens frame is fixedly provided with a lens, the front side of the lens frame is provided with a rotating groove, the rotating groove is rotatably provided with a ring plate, the outside of the ring plate is provided with a limiting assembly for limiting the ring plate in the rotating groove and preventing the ring plate from falling out, and the top of the ring plate is fixedly provided with a stand column. The application can accurately adjust the position of the eyeball of a patient, position the eyeball by the close observation of the patient on the bottom end of the indicating sheet, facilitate the observation and detection of the eyeball, magnify the eyeball through the lens, facilitate the careful observation of the eyeball, and facilitate the adjustment of the angle of the lens according to the needs, so as to meet the observation needs.

The invention relates to a fatigue driving detection method, a terminal, a server and a readable storage medium, and the method comprises the steps: obtaining video data collected by a visual sensor used for monitoring a target object, carrying out the facial feature detection of the video data, and obtaining the eye state information and mouth state information of the target object; determining a fatigue state type of the target object according to the eye state information, and determining a fatigue state type of the target object according to the mouth state information; if the target object is in the suspected fatigue state, uploading sub-video data when the target object is in the suspected fatigue state to a server, so that the server executes a fatigue detection process according to the sub-video data to determine fatigue state information of the target object; and receiving fatigue state information of the target object returned by the server. According to the method, the terminal and the server can jointly detect the fatigue state, and meanwhile, the accuracy and recall rate of fatigue state detection are guaranteed.

The application provides a bullet cabinet with alcohol detection function, and the alcohol detection system comprises: a data acquisition module which acquires detection video of a cabinet opening personnel through a camera, acquires detection voice of the cabinet opening personnel through a microphone, acquires historical cabinet opening data, and acquires current time data; a personnel state determination module which processes the detection video, the detection voice, the historical cabinet opening data, and the current time data to obtain a face alcohol state score, an eye state abnormality score, a body action amplitude score, a voice instability score, and a time risk score; a risk index determination module which determines a final risk index according to the face alcohol state score, the eye state abnormality score, the body action amplitude score, the voice instability score, and the time risk score; and a cabinet lock control module which controls the opening and closing state of an intelligent cabinet lock according to the final risk index. The alcohol detection precision of the cabinet opening personnel is improved, and the risk of using a gun by the cabinet opening personnel is improved.

The invention discloses a vehicle-mounted intelligent monitoring method and system based on multi-mode communication and behavior recognition, and relates to the related field of vehicle-mounted electronics and computer vision, the method adopts multi-mode communication to upload the acquired network signal intensity, vehicle driving state and cab real-time image and video data to the system, and the system is used for monitoring the behavior of the vehicle. Network signal strength changes are predicted according to historical data, and a multi-factor decision strategy is made to automatically switch communication networks; a pre-training target detection model adaptive to a night light environment is applied to position a face area of a driver, face key points are obtained through key point detection, dynamic fatigue characteristics of the driver are tracked in a cross-frame mode in combination with a target tracking algorithm, the eye state, the head posture and the yawning behavior of the driver are analyzed, and the fatigue index of the driver is calculated. And the vehicle driving safety is guaranteed through layered early warning. The problems that an existing vehicle-mounted intelligent monitoring system is single in communication mode, and a fatigue driving detection model embedded in the system cannot accurately position the face area of a driver are solved.

The invention discloses a display adjustment method and device, electronic equipment and a computer readable storage medium. The display adjustment method comprises the steps that eye state information of a target object is acquired; wherein the eye state information at least comprises eye fatigue and a sight line position; in response to the fact that the eye fatigue degree is larger than a preset fatigue degree threshold value, display parameters of part or all of the display content at the sight line position are adjusted so as to reduce the eye fatigue degree; wherein the display parameters at least comprise at least one of the size, the style, the color, the brightness and the contrast ratio of the display content. Based on the mode, the display effect of the display equipment can be effectively improved, so that the user experience is improved.

The application relates to the technical field of brain detection, and particularly discloses a test auxiliary system and method for brain diseases, wherein the system comprises an automatic control module, a light source control module and a data synchronization module. The automatic control module is used for inputting an open-closed eye test rule, converting the open-closed eye test rule into a light period control rule, and generating an open or off light instruction according to the light period control rule. The light source control module is used for controlling the switch state of an access light source according to the open or off light instruction, so as to simulate an open eye state and a closed eye state. The data synchronization module is used for acquiring environment brightness data and light source switch state data, and is also used for acquiring an electroencephalogram from an electroencephalogram test device and generating a visual report of the open-closed eye test. The technical scheme of the application can effectively solve the problem that a patient with a brain problem found in a nuclear magnetic resonance examination does not cooperate in an open-closed eye test, and improve test accuracy.

The application relates to a line-of-sight calibration, motion tracking and precision testing method based on adaptive time sequence analysis prediction, which specifically comprises the following steps: through image color recognition technology, color blocks and calibration point positions in a screen are recognized in a scene image, the actual size of the screen is combined, and the screen position is roughly positioned; distortion calibration is carried out based on the calibration point information, the screen position is precisely positioned, and the mapping relationship between the scene image and the precisely positioned screen is determined; eye control type nine-point calibration is carried out, the mapping model of the eyeball physical information and the gazing space position of the tester is determined, the screen gazing point coordinates are obtained in combination with the mapping relationship; line-of-sight positioning precision quantitative testing is carried out; through an adaptive time sequence analysis prediction algorithm, the current line-of-sight positioning is optimized and the future gazing point position is predicted in combination with historical line-of-sight information, meanwhile, the parameters in the time sequence analysis prediction algorithm are adaptively adjusted according to real-time precision or the intensity of shaking; through an eye state detection algorithm, the state of the human eye in the open and closed eye state is detected, and eye movement control is carried out.

This application discloses a device control method, apparatus, electronic device, and computer-readable storage medium, relating to the field of computer technology. The method includes: receiving raw electroencephalogram (EEG) signals of a target user collected by a signal detection device, and acquiring the raw operating state of an Internet of Things (IoT) device; performing frequency domain conversion processing on the raw EEG signals, and determining the target user's eye state information in the frequency domain based on the converted signal data; adjusting the operating state of the IoT device based on the eye state information, the raw operating state, and a preset state adjustment relationship, thereby achieving rapid and stable adjustment of the IoT device's operating state based on the user's actual eye state, with high applicability.

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 discloses a drunkenness state detection method, system and device and a medium, and the method comprises the steps: obtaining the eye data of a driver in a preset time period, and enabling the eye data to comprise eyeball state data; performing time domain feature extraction on the eyeball state data to obtain time domain feature data; performing frequency domain feature extraction on the eyeball state data to obtain frequency domain feature data; fusing the time domain feature data and the frequency domain feature data to obtain eyeball tremor feature information; and based on the eyeball tremor characteristic data, utilizing a neural network model to detect the drunkenness state of the driver. Through fusion of frequency domain and time domain feature information, the eyeball tremor state of the driver is evaluated from multiple features, the robustness of data and the generalization ability of a model can be improved, and the drunk driving state detection precision is improved. And the judgment result can be fused with a drunkenness state detection result based on the physiological feature information of the driver and the vehicle state information, so that the accuracy of deducing the drunkenness state of the driver is further improved.

The utility model discloses an anti-dizziness driving simulator which comprises a simulator body, an arc-shaped shell is arranged at the upper end of the simulator body, an arc-shaped limiting rod is arranged in the arc-shaped shell, a supporting shell is connected to the interior of the arc-shaped shell in a sliding mode, a first limiting opening is formed in one end of the supporting shell, and an arc-shaped rack is arranged in the arc-shaped shell. One end of the supporting shell is rotatably connected with a gear, a second limiting opening is formed in one end of the supporting shell, a spherical limiting block is rotatably connected into the second limiting opening, a limiting hole is formed in the outer side of the spherical limiting block, a camera is arranged in the limiting hole, a sliding groove is formed in the supporting shell, and an electromagnet is arranged in the sliding groove; a sliding block is slidably connected into the sliding groove, a magnetic block is arranged at one end of the sliding block, a driving rod is rotatably connected into the supporting shell, and one end of the driving rod is rotatably connected with a connecting rod. According to the utility model, the camera can be adjusted more flexibly, the eye state of a driver can be monitored better, and the dizziness of the driver can be eliminated in time.

Methods, systems, and storage media for projecting multi-viewer-specific 3D object perspectives from a single 3D display are disclosed. Implementations may: acquire face and eye region image data of a plurality of viewers within a field of view of at least one camera associated with a 3D-enabled digital display; analyze the eye region image data to determine at least one 3D eye position, at least one eye state, at least one gaze angle, and at least one point-of-regard for at least one viewer relative to at least one camera associated with the 3D-enabled digital display; and calculate a plurality of image projections for display by the single 3D display.

The invention discloses a control method and device of wearable equipment, equipment and a storage medium, relates to the technical field of wearable equipment, and discloses the control method of the wearable equipment, the control method of the wearable equipment is applied to the wearable equipment, and the wearable equipment is provided with an image acquisition device. The image acquisition device is used for monitoring an eye state; the method comprises the following steps: analyzing a user eye image acquired by an image acquisition device, and determining a user eye state; when the eye state of the user is an eye closing state, state duration is determined; and when the state duration exceeds a target duration threshold, controlling the wearable device to enter a power-saving mode. By means of the mode, when it is detected that the user enters the sleep state, the equipment automatically enters the power saving mode, the cruising ability of the wearable equipment is improved, and the use experience of the user is improved.

The invention relates to the technical field of eye detection, and discloses a cornea contact cap assembly for eye detection, the cornea contact cap assembly comprises a protection mechanism and a driving mechanism, the arranged protection mechanism can carry out risk protection on eyes of a patient in the eye detection process of the patient, the damage to the eyes of the patient due to movement is avoided, and the safety of the patient is improved. Meanwhile, the microscope is driven to perform the same movement according to the movement distance of the patient, the detection effect is prevented from being affected by excursion of the examination position, the arranged driving mechanism can prevent the cornea contact cap from performing high-strength compression on one vertex of an eyeball to the maximum extent when the eyes of the patient are examined, the detection end abutting against the eyes is concave, and the detection effect is improved. The cornea contact cap is attached to the eyeball, the abutting pressure of the eyeball is reduced, meanwhile, the eye state of the eyeball in the normal state can be observed more clearly, the adaptability of a patient is improved, meanwhile, the arranged driving mechanism can prevent a doctor from repeatedly smearing a new cornea contact cap, and the bacterial infection risk is reduced while the working efficiency is improved.

The application discloses a background activity automatic identification method and system based on resting state electroencephalogram (EEG), which automatically identifies the EEG signals of a patient in a closed-eye state in different regions, extracts EEG features of each region and each frequency, analyzes and compares the EEG features by referring to a standardized range, and finally outputs the identification and analysis results as a visual report, so as to facilitate quick manual verification, online editing and modification when necessary, realize the efficiency of EEG automatic interpretation, guarantee the accuracy of result analysis, provide a possibility of interpreting high-dimensional data information from original two-dimensional EEG efficiently and quickly, and provide a potential technical means for non-EEG professionals who are not familiar with EEG data analysis and processing. The application can realize the automation of the identification process, improve the identification efficiency, thereby reducing heavy and repetitive mechanical labor, facilitating medical staff to analyze and judge the result report, improving the work efficiency, and saving the labor cost.

The invention discloses a fatigue driving detection method, system and device and a medium, and the method comprises the steps: collecting a driving image of a driver, carrying out the preprocessing of the driving image, and recognizing a mask shielding state; positioning facial features of the driver, locking eye angular point positioning based on a facial contour, intercepting eye and mouth area images, sending the area images into a built identification model, and obtaining eye states and mouth states; according to the eye state and the mouth state, the fatigue degree of the driver is recognized by fusing multi-dimensional data, and driving reminding is given based on the recognition result. According to the method, the eye and mouth areas are positioned through the face frame and eye corner coordinates, the eye and mouth area images are intercepted and corrected, and the images are used as input to be transmitted to the eye and mouth state recognition model constructed based on the convolutional neural network, so that the fatigue degree of a driver is recognized, the traffic accident risk is effectively reduced, fatigue driving is avoided, and the driver experience is improved. And the occurrence rate of traffic accidents is reduced from the source.

The present application provides an eye state evaluation method and an electronic device. The method comprises: obtaining an optic disc image region from a first fundus image, and generating a plurality of optic cup disc ratio evaluation results based on the optic disc image region by a plurality of first models; obtaining a first evaluation result of the eye based on the optic cup disc ratio evaluation results; performing a plurality of data augmentation operations on the first fundus image to generate a plurality of second fundus images; generating a plurality of optic nerve fiber layer defect evaluation results based on the second fundus images by a plurality of second models; obtaining a second evaluation result of the eye based on the optic nerve fiber layer defect evaluation results; and obtaining an optic nerve evaluation result of the eye based on the first evaluation result and the second evaluation result. Thus, the present application can provide a reference for doctors when evaluating the eye state of patients, thereby helping doctors to give appropriate evaluation results for the eyes of patients.

Embodiments of the present application disclose a face recognition method and device, a terminal device and a storage medium. The method is applied to the terminal device, and includes: obtaining a face image in a preset time period, and determining an eye region from the face image; detecting a luminance value corresponding to the eye region at each unit time, and determining an eye state corresponding to the eye region at each unit time according to the luminance value corresponding to the eye region at each unit time, wherein the unit time is any time in the preset time period; and when the eye state corresponding to the eye region in the preset time period changes, determining a face in which the eye region is located as a live face. The embodiments of the present application accurately recognize a live face in an image, especially in the case that multiple faces exist in the image, thereby providing a basis for subsequent optimization of the image.

This application relates to the field of computer technology, and particularly to the field of artificial intelligence technology. It discloses a method, device, equipment and storage medium for image optimization and rendering to solve the problem of poor image rendering effect. The method includes: determining the actual eye region from the acquired image to be processed, and based on each first eye key point included in the actual eye region, adjusting the shape of the standard eye region including the virtual makeup effect to obtain a simulated eye region including each second eye key point, so that each first eye key point corresponds to each second eye key point one by one; based on the eye state corresponding to the actual eye region, extracting the corresponding rendering materials from the simulated eye region, and in the image to be processed, performing fusion rendering processing on each second eye key point included in the rendering materials and the corresponding first eye key point respectively to obtain the target image. This improves the fitting degree of the simulated eye region and the overall rendering effect.

The application discloses an eyeball depth image repairing method, system and device, and the repairing method comprises the following steps: acquiring an open-eye color image, an open-eye depth image, a closed-eye color image and a closed-eye depth image; respectively extracting key points from the open-eye color image and the closed-eye color image to obtain open-eye key point information and closed-eye key point information; respectively extracting depth information from the open-eye depth image and the closed-eye depth image according to the open-eye key point information or the closed-eye key point information to obtain open-eye depth information and closed-eye depth information; obtaining a position conversion matrix between the open-eye color image and the closed-eye color image according to the open-eye key point information and the closed-eye key point information; and obtaining an eyeball depth image of the repaired eyeball to be repaired according to the open-eye key point information, the open-eye depth information, the closed-eye depth information and the position conversion matrix. Through alignment and fusion of the closed-eye depth information and the open-eye depth information, the problem that the depth data is incomplete in an open-eye state is effectively solved.

The invention provides a display device and a playing control method based on a user watching state, and the method comprises the steps: collecting first image data at a media asset video playing time interval in response to a starting instruction of a preset interaction function, and executing face recognition through a first network model, and when the face image data is recognized, head posture information and eye state information are determined through a second network model, then the staring state of people on the display screen is judged according to the information, and when all people do not watch the display screen, playing of the media asset video is paused in response to the first target control instruction. By sensing the staring state of the user on the display screen, the limitation that the display device depends on the user to actively input the control instruction can be solved, so that the display device can actively sense the staring state of the user to suspend playing of the media asset video, the user is prevented from missing the media asset video, and the interaction intelligence of the display device is improved.

The invention relates to the field of eye detection, and discloses a three-dimensional model construction method based on ophthalmology detection, which comprises the following steps: firstly, collecting human eye state information, and preprocessing the human eye state information to obtain preliminary eye state information; performing data analysis on the initial eye state information, and determining initial parameters of an eye three-dimensional model; performing parameter optimization to obtain screening parameters of the eye three-dimensional model; establishing an eye three-dimensional model, collecting eye key points in the eye three-dimensional model, and binding eye screening point data for the eye key points; performing normalization processing on the eye key points, and performing screening operation through big data comparison to obtain final eye state information; geometric structure reconstruction is carried out to obtain a reconstructed eye three-dimensional model; the problems that in the prior art, eye detection is not accurate, the diagnosis result is prone to being affected, and an existing eye model is greatly different from the actual eye size, position and shape of a patient are solved.

A contact lens (100) is provided. The contact lens (100) comprises at least one sensor 8101 which is operative to capture sensor data indicative of a transition of the contact lens between an on-eye state and an off-eye state, and processing circuitry (102). The processing circuitry (102) is operative to store information pertaining to a user of the contact lens (100), detect a transition of the contact lens (100) from the on-eye state to the off-eye state, based on sensor data captured by the at least one sensor (101), and in response to detecting the transition from the on-eye state to the off-eye state, protect the stored information against unauthorized access. Thereby, potentially private and / or sensitive information such as health-related information is prevented from unintended dissemination if the contact lens (100) is lost or displaced.

The application provides a shooting method based on open and close eye detection and an electronic device. After detecting a shooting operation, the electronic device with shooting capability such as a mobile phone or a camera can determine the eye state of an image sequence corresponding to the shooting operation, determine a preferred image and one or more backup images from the image sequence, then display the preferred image and the backup image, and retain one image from the preferred image and the backup image according to a user operation. In this way, the electronic device can improve the shooting experience of the user, so that the user can take photos in accordance with the intention, and the memory of the electronic device is not occupied.

The invention relates to an intelligent health bed integrating AR eye movement training and self-adaptive massage and a control method thereof.The intelligent health bed comprises a massage bed body which is integrated with at least one massage unit and used for massaging at least one of the neck, the shoulders, the back, the waist and the legs of a user; the eye relaxation module comprises wearable AR glasses or a bed body built-in display screen and is used for presenting eye relaxation contents to the user; the sensor module is used for collecting posture data, physiological data and eye state data of a user in real time; the massage bed has the advantages that the two functions of AR eye movement training and body self-adaptive massage are deeply fused in a single lying scene, and by means of synchronous and cooperative control of the control module, the two functions of AR eye movement training and body self-adaptive massage are achieved; the nerve visual fatigue and the body muscle fatigue of the user can be relieved at the same time during one-time rest, and the rehabilitation efficiency and the integrity and comfort of user experience are improved.