43 results about "Eye state" patented technology

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 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 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 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 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.

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.

The application provides an eye key point detection method, an eye state detection method and related devices, including: obtaining a face image of a to-be-detected object; inputting the face image into a pre-trained eye key point detection model, wherein the pre-trained eye key point detection model includes a backbone network, a first key point branch network and a second key point branch network; performing feature extraction on the eye region through the backbone network to obtain eye features; predicting a first key point through the first key point branch network according to the eye features, wherein the first key point is an eye key point of a predetermined part; and predicting a second key point through the second key point branch network according to the eye features and feature information corresponding to the first key point. The application can improve the accuracy of eye key point detection and reduce the false detection rate.

A driving safety control method, comprising: on the basis of eye state information of a driver and outside environment information of a vehicle, determining whether the eyes of the driver meet a field of view compensation trigger condition; and on the basis of the outside environment information of the vehicle, generating a driver field of view compensation image and providing same to the driver. The driving safety control method realizes the field of view compensation for the driver when the vision is limited or the field of view is insufficient, and effectively solves the problem of the vision being limited in complex scenarios such as light change, front windshield (5) obstruction, and severe weather, thereby improving the perception capability of the driver, reducing the risk of traffic accidents, and ensuring the driving safety of the driver. Further comprised are an electronic device (110), a storage medium, and a vehicle (100).

The application provides a dim environment closed-eye detection method and system, and belongs to the technical field of computer vision detection.The dim environment closed-eye detection method is characterized in that the following steps are included: setting a lower threshold value and an upper threshold value, wherein the lower threshold value and the upper threshold value are both positive numbers, and the lower threshold value is smaller than the upper threshold value; receiving a video frame, calculating an EAR according to eye key point coordinate information; judging the EAR according to a double threshold method, and when a plurality of continuous frames meet the set condition, the closed-eye state is determined, wherein the execution method of the double threshold method includes: judging the EAR value, if the EAR value is smaller than the lower threshold value, starting counting, and if the EAR value is smaller than the upper threshold value, the number of times is accumulated, if the EAR value is not smaller than the upper threshold value, stopping and resetting the counting, and when the number of times reaches the set threshold number of times, the closed-eye state is determined.The application has the beneficial effect that the closed-eye state can be stably and accurately detected in a dim environment such as a mine, thereby providing support for a fatigue driving detection system.

This disclosure relates to the field of terminal control, specifically to an eye state detection method, device, wearable device, and storage medium. The eye state detection method includes: continuously collecting the wearer's periocular electromyography (EMG) signals and corresponding actual posture information during wearable device operation; determining the wearer's wearing displacement state based on a comparison of the actual signal characteristics of the periocular EMG signals with preset reference EMG signal characteristics, and / or the actual posture information; if a wearing offset is determined, correcting blink detection parameters or eye movement detection parameters based on the current periocular EMG signals; and performing eye state detection on the wearer based on the corrected blink detection parameters or eye movement detection parameters. It can autonomously trigger the correction of blink detection parameters or eye movement detection parameters without human intervention, effectively ensuring the wearable device's responsiveness and system stability.

The invention discloses a low-flicker adaptive backlight control device and method, and relates to the technical field of backlight control of display equipment. The device comprises a multi-source sensing cooperation module, a main control processing unit, a dynamic threshold dual-dimming driving unit, a backlight module and a storage unit which are electrically connected in sequence, multi-dimensional parameters such as ambient light, screen content brightness and user eye states are synchronously collected through a multi-source sensing cooperation module; the main control processing unit calculates target brightness based on a scenarized weighted fusion model and a machine learning algorithm, and ensures output stability through PID dynamic compensation; the dynamic threshold dual-dimming driving unit dynamically adjusts the switching threshold of PWM dimming and similar DC dimming according to the change rate of ambient light and the fatigue state of a user, so that smooth flicker-free brightness transition is realized; the problems of low-brightness stroboflash, brightness jump, poor scene adaptability, dimming lagging and the like in the prior art are effectively solved, and flicker-free, smooth and personalized automatic backlight control is realized.

This invention proposes a multi-feature adaptive fatigue detection method and system for inland waterway crew members in complex environments, relating to the fields of computer vision and intelligent navigation safety. It includes a video enhancement preprocessing module, a spatiotemporal fatigue feature extraction module, an individual adaptive judgment module, and a system integration output module. On a shipborne edge computing device, a "Collaborative Reflectance Perception Low-Light Enhancement Network CRL-Net" is designed to address the data degradation problem in low-light and strong reflective environments. An "End-to-End Spatiotemporal Fatigue Feature Learning Network RMT-3DCNN+LSTM" is designed to achieve the fusion extraction of three types of features: pupil movement, eye state, and fatigue expression. Combining AIS system data and individual crew member alertness benchmarks, a dual-branch adaptive weighting mechanism is used to determine and warn of fatigue status. This invention achieves accurate adaptive detection of crew member fatigue status in complex inland waterway navigation scenarios, providing an efficient and reliable intelligent monitoring solution for improving the navigation safety of inland waterway vessels.

A method and a monitoring device determine a binary eye state of a person. In the process, a monotonically decreasing slope with at least one specified minimum height is determined in a time curve of an eyelid gap which is determined in a camera-based manner. A current transition threshold for a change between an open and a closed eye is determined as a specified percentage value of the distance between the average value of a number of starting points of decreasing slopes and an average value of a number of corresponding end points. The eye is detected as being closed if the current eyelid gap is smaller than the current transition threshold. A monotonically increasing slope in the eyelid gap curve which has at least one specified minimum height is determined starting from the last end point. The eye is detected as being open if an end of the current increasing slope has been reached.

This application provides a method, device, medium, program product, and terminal for autonomous driving eye monitoring based on facial projection transformation and visual projection. By acquiring driver image data and driving operation data in real time, and combining facial projection transformation and 3D model construction, the accuracy and reliability of driver state monitoring are significantly improved. It effectively corrects image displacement and distortion caused by driver head movement and posture changes, ensuring accurate facial information recognition. The coarse and fine eye positioning coordinates generated based on facial projection enable accurate monitoring of eye opening and closing in complex situations, thereby identifying driver fatigue. Furthermore, by constructing a 3D head model, the driver's posture at different angles can be analyzed, further enhancing monitoring accuracy. Intelligent warning commands generated by combining driving operation data and eye state can promptly alert the driver to potential safety risks, thereby effectively improving driving safety.

The application provides an eye state detection method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a to-be-processed image, and acquiring a target region image from the to-be-processed image, wherein the target region image comprises an eye region image and an eye surrounding region image, the eye surrounding region image is used for representing an image in a set region around the eye, then the eye region image and the eye surrounding region image are identified to obtain an identification result of the target region image, finally, the detection result of the eye state in the to-be-processed image is determined according to the identification result. The method can acquire the eye region image and the eye surrounding region image regardless of whether the driver wears glasses or not, and the identification results of the two images are fused to determine the state of the eye in the to-be-processed image, so that the eye state of the driver can be accurately detected.

This invention discloses a VR-based system for generating and interacting with psychological support scenarios for end-stage patients, relating to the field of scenario simulation and interaction. The system includes: a scenario acquisition module for providing users with several types of preset indicator scenario data; a state acquisition module for acquiring facial and eye state feedback images when users experience a preset indicator scenario data; a feature extraction module for performing sentiment analysis on the state feedback images to extract emotional features, and combining this with the user's corresponding language text to extract key semantic features; and a preference analysis module for constructing a preference analysis model using deep learning algorithms. The model takes emotional and semantic features as input and outputs a user preference coefficient for the preset indicator scenario. By dynamically calculating the scenario preference coefficient, the system ensures that recommended content highly matches the patient's current psychological state, adaptively adjusts the dimensions of the AR simulation framework, forms a coherent and personalized experience, and improves the effectiveness of psychological support.

The application discloses a kind of fatigue detection methods based on driver face recognition, including the driving image is input to the face extraction neural network model of pre-set and is identified, obtains global face image and local eye area image;Global face image is input into lightweight neural network, and global feature map is obtained, and local eye area image is input into lightweight neural network, and double local feature map is obtained;Global feature map is input into global feature extraction model and is extracted, and global feature information is obtained, and the first eye feature map and the second eye feature map in double local feature map are fused and analyzed, and local feature information is obtained;Global feature information and local feature information are subjected to multiple fusion processing, and the eye state of driver is classified according to processing result, to determine the fatigue degree of driver and issue warning, guarantee traffic safety.

The application provides an eye movement interaction method, device and electronic equipment. When it is determined according to eye lid data that the user's eyes are in an abnormal open-eye state, the visual depth of the user's eyes is adjusted, and a plurality of objects to be selected under the adjusted visual depth are obtained. When it is determined according to eye lid data that the user's eyes are in a normal open-eye angle and the gaze direction has not changed within a preset time period, the gaze point of the user's eyes in the gaze direction within the preset time period before the current time is obtained. According to the gaze point of the user's eyes in the gaze direction, the target object gazed at by the user's eyes is determined, the visual depth is adjusted by using the eye lid data, and in the case that the plurality of objects to be selected under the adjusted visual depth are obtained, the selection of the target object gazed at by the user is further performed. The triggering condition of the program for adjusting the visual depth is determined, and the program for adjusting the visual depth is prevented from being mistakenly triggered in the process in which the user normally watches images by using a wearable device such as a VR device.

The utility model provides a contact lens which comprises a rear surface facing an eyeball when worn, a front surface opposite to the rear surface and a tear channel, and the tear channel extends in the radial direction of the contact lens along the rear surface or the front surface. By the adoption of the structure, the contact lens can be rotated through tears, the contact lens can be rotated through flowing of the tears no matter in the daytime or at night, no matter a wearer is in the eye using states such as working and learning or in sleep and rest (including the rest at any time such as noon break), and therefore the applicability of the contact lens technology is improved.

The embodiment of the present application provides a kind of fatigue detection method, device and readable storage medium.The fatigue detection method of the embodiment of the present application: by obtaining the eye image of driver, eye image is input into target convolutional neural network, to obtain the eye state information contained in eye image, eye state information is used to indicate the opening degree of the eye of driver, target convolutional neural network is obtained by using the eye image sample collected in advance to train convolutional neural network, according to the eye state information contained in each of the multiple frames of eye image of driver, whether driver is in fatigue state is determined.Thereby it can be more easily determined whether driver is in fatigue state, and by target convolutional neural network, whether driver is in fatigue state can be realized in real time.

1. Name of the designed product: eye movement tracking computer (AIO-01 type). 2. Use of the designed product: used for obtaining eye state and line of sight information. 3. Design points of the designed product: in shape. 4. Picture or photo best indicating the design points: perspective view 1.

This application provides a method, device, electronic device, and storage medium for detecting eye state. When a target object is learning target content displayed in a target area of ​​a learning interface, eye movement data of the target object on the display screen is acquired. The eye movement data includes at least one of fixation stability and gaze deviation data. The target object's eye state is then determined based on the eye movement data, indicating either a non-fatigue state or a fatigued state. Thus, by comprehensively determining the target object's eye state using eye movement data such as fixation stability and / or gaze deviation data, the degree of jitter and deviation of the gaze position within the target area can be accurately quantified, thereby more accurately reflecting and identifying the target object's true fatigue level and improving detection results.

The application provides a control method for an intermediate coil type of a hot coil box and related equipment, and relates to the technical field of hot coil boxes. The method comprises the following steps: acquiring an inner ring coil eye state of a coiled intermediate product, wherein the coiled intermediate product is formed by a bending operation, a correction operation, a supporting operation and a stabilizing operation of an intermediate strip in a hot coil box, and the intermediate strip is guided into a roller bed of the hot coil box by an inlet side guide plate; and formulating a bending roller gap adjustment strategy based on the inner ring coil eye state of the coiled intermediate product.

The utility model discloses a BJD (ball joint doll) doll head shell structure comprising independent opening and closing eyelids and a detachable eye piece assembly, and belongs to the technical field of toy dolls, namely a ball joint doll. Holes are formed in the eyes of an existing BJD doll head shell without eyelids. A pair of pivot seats is arranged on the inner side of the face shell, the middle pivot seat is used for fixing inner pivots of the eyelids, the left pivot seat and the right pivot seat are used for fixing outer pivots of the eyelids, the eyelashes are located below the eyelids and clamped in eye frames of the face shell to limit turning of the eyelids, the turning angle is right between the eye closing state and the eye opening state, and the left eyelids and the right eyelids are independently controlled to be opened and closed around the axes. The eye sheet is fixed on the eye sheet plate, and the eye sheet plate is detachably mounted at the insertion position on the eye sheet baffle; the eye sheet baffle is inserted into the anti-rotation positioning groove through the positioning column and is inserted into the face shell; the eyelids of the BJD doll can be independently opened and closed, the eyelids can be quickly replaced, and the BJD doll is adaptive to diversified head shell designs.

The present application provides a fatigued driving detection method and apparatus, an electronic device, and a readable storage medium. The method comprises: during the process of a driver driving a vehicle, acquiring in real time a facial image of the driver; on the basis of a first opening degree of eyes in the facial image, determining the eye state of the driver, wherein the eye state comprises an open‑eye state and a non‑open‑eye state, and the non‑open‑eye state comprises a closed‑eye state and a downward‑looking state; when the eye state of the driver in the facial image is the non‑open‑eye state, identifying a head change trend of the driver on the basis of multiple consecutive first facial images corresponding to the facial image, wherein the head change trend comprises a gaze direction change trend and / or a brow center position change trend; on the basis of the head change trend of the driver, determining the non-open-eye state of the driver to be the closed-eye state or the downward-looking state; and if the driver is in the closed‑eye state, determining the driving state of the driver to be a fatigued driving state. The method improves the accuracy of fatigue state detection.

This invention discloses an eye pose recognition method based on close-range photogrammetry, comprising: step 101, locating facial feature points in two images from two binocular cameras; step 102, using the facial feature points from the two images as corresponding points, recovering the three-dimensional coordinates of the facial feature points using close-range photogrammetry and the least squares algorithm; step 103, extracting the three-dimensional coordinates of the eye region feature points and reprojecting them onto the XOY plane; step 104, calculating the head pose angle using the three-dimensional coordinates of the facial feature points, and using the head pose angle to correct the EAR value. Beneficial effects: The EAR value calculated based on the projection of the three-dimensional coordinates onto the XOY plane does not need to consider the error caused by the yaw angle. Furthermore, by using the three-dimensional coordinates of the facial feature points to calculate the head pose angle to correct the EAR value, the EAR value does not change significantly regardless of the change in the pitch angle γ between two consecutive frames, thus providing a good indication of the eye state.

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.