9 results about "Eye blink" patented technology

The embodiment of the invention is applied to the field of artificial intelligence, and provides an image processing method and electronic equipment, and the image processing method comprises the steps: obtaining a first image set, the first image set comprises multiple frames of first images, and each frame of first image records a human face; determining a face image and an eye image in each frame of the first image; determining posture information of the human face recorded in each human face image, and obtaining posture information corresponding to each human face image; through a blink detection model, based on set data corresponding to the first image set, a detection result corresponding to the first image set is determined, and the detection result corresponding to the first image set indicates whether blink actions are recorded in the multiple frames of first images or not; the set data corresponding to the first image set comprises the face image and the eye image of each frame of first image in the multiple frames of first images and the posture information corresponding to each face image. Based on the technical method provided by the invention, the accuracy of the detection result of the blink action can be improved.

An eye blink detection method and system are disclosed. The eye blink detection method comprises: photographing a face using a DVS camera to obtain a stream of DVS pixels; integrating DVS pixels of the stream of DVS pixels to form a plurality of DVS frames, wherein each of the plurality of DVS frames comprises a plurality of first and second color pixels, each being associated with one or more DVS pixels indicating a brightening event and each of the second color pixel being associated with one or more DVS pixels indicating a darkening event; and determining whether there exists an eye blink action in a DVS frame of the plurality of DVS frames, wherein the determining comprises: determining whether there exists a pattern in which a first and second color region are distributed one above the other in an eye region of the at least one DVS frame.

A method for assessing fatigue of a subject is provided. The method includes providing a device comprising a first electrode, a second electrode, and a circuit operably coupled to the first and second electrodes, the first and second electrodes configured to detect an electrical activity associated with an eye blink of a subject, and the circuit is configured to process a signal from the first electrode and the second electrode; determining a blink event based on the electrical activity; and assessing a degree of fatigue of the subject, based on the blink event. A headset including circuitry, such as a processor and a memory storing instructions to cause the headset to perform the above method are also provided. Also provided are systems and kits that include the devices. The methods, devices, headsets, systems and kits find use in a variety of different applications.

The application provides an eye blinking detection method and device based on a dynamic threshold, equipment and a storage medium. The eye blinking detection method based on the dynamic threshold comprises the following steps: S1, acquiring an electromyographic signal set; the electromyographic signal set comprises electromyographic signals of an eye region of a user corresponding to a current time window and / or at least one time window before the current time window; S2, extracting an eye blinking feature parameter of each electromyographic signal in the electromyographic signal set; S3, updating an eye blinking detection threshold based on the eye blinking feature parameter; and S4, performing eye blinking detection by using the updated eye blinking detection threshold. The method can dynamically update the eye blinking detection threshold based on the electromyographic signals of the user, realize adaptive adjustment of the threshold, and help improve the accuracy of detecting eye blinking of the user.

An electronic device capable of estimating a user's situation is to be provided. The electronic device includes a camera, a processing portion, and a display portion. The camera has a function of capturing an image of a user's eye and his / her periphery repeatedly to generate a plurality of pieces image data. The processing portion has a function of detecting, from the plurality of pieces of image data, a change over time in information including at least one of a frequency of eye blinks, a time taken for one blink, a distance between an upper eyelid and a lower eyelid, a sight direction, and an area of a pupil, a function of estimating a level of user's eye fatigue on the basis of the change over time in information, and a function of generating string information in accordance with the estimated level of user's eye fatigue. The display portion has a function of displaying string information.

A method for identifying an occurrence of a concussion in a subject involves capturing eye blink raw data from at least one eye of the subject. The method next involves analyzing the eye blink raw data to generate at least a first subject specific eye blink metric and determining that a significant difference exists between the first subject specific eye blink metric and a predefined normal value. Next, the occurrence of the concussion in the subject may be identified, based on determining that the significant difference exists.

A computer controls a recording device within a contact lens environment. The computer receives a video signal from a Video Recording Device (VRD) within a contact lens environment proximate an eye of a user. The computer controls the VRD, and the video signal provides a substantially real-time representation of a monitored zone. The computer receives eye blinking metadata for the user and generates a blinking pattern using a machine learning model trained to determine eye blinking patterns from metadata. The computer establishes a recording routine characterized by periods of recording and pausing substantially synchronized to the blinking pattern. The computer directs, in response to receiving a start signal, the VRD to record the video signal in accordance, at least partially, with the recording routine. The computer identifies within the video signal, a recording modification trigger condition and initiating a corrective action in response thereto.

A real time system for monitoring and optimizing patient adherence to digital therapy. The system can measure at least one of head stability, eye stability, gaze direction, head pose, facial expression, reading related eye movements, eye alignment stability, eye blink rate, attentive engagement, general engagement, emotional state, total eye stability, yawning and distance between the user and the camera. This information is provided as input to computer vision algorithms to generate a multi-dimensional representation of user attention and engagement. The system can alert the caregiver or health care professional if the patient disengages from the treatment and if the patient is sitting at the wrong distance from the treatment device. The system includes a camera, a processor, computer vision algorithms executed by the processor (a GPU processor), at least one digital display device, a loud speaker and an optional internet connection that can enable communication with other electronic devices.

The invention belongs to the technical field of aviation, and particularly relates to a pilot emotion awakening method and system based on eye movement, and the method comprises the steps: collecting the real-time eye movement information of a pilot, and the eye movement information at least comprises the blinking time and the pupil diameter; acquiring current flight stage information and identity information of the pilot; based on the identity information and the current flight stage information, physiological limit values corresponding to the pilot are called, and the physiological limit values comprise a blink duration physiological limit value and a pupil diameter physiological limit value corresponding to the current flight stage; the real-time eye movement information is compared with the physiological limit value, and the current emotional state of the pilot is judged according to the comparison result; when it is judged that the pilot is in the negative emotional state, an alarm instruction is generated and executed to remind the pilot.