294 results about "Eye detection" patented technology

A gaze direction determining system and method is provided. A two-camera system may detect the face from a fixed, wide-angle camera, estimates a rough location for the eye region using an eye detector based on topographic features, and directs another active pan-tilt-zoom camera to focus in on this eye region. A eye gaze estimation approach employs point-of-regard (PoG) tracking on a large viewing screen. To allow for greater head pose freedom, a calibration approach is provided to find the 3D eyeball location, eyeball radius, and fovea position. Both the iris center and iris contour points are mapped to the eyeball sphere (creating a 3D iris disk) to get the optical axis; then the fovea rotated accordingly and the final, visual axis gaze direction computed.

In an eye detection method, a plurality of candidate eyes are located within a digital image. Pixels of interest having a predetermined characteristic and a predetermined association to respective eyes are found. Pixels of interest associated with each eye are grouped. Parametric boundaries are fit on each of the groups to define a plurality of detected eye features. The boundaries have a predefined uniform shape and a size matched to a respective group. Each of the detected eye features is scored as to a geometric relationship between the respective boundary and pixels of interest associated with the respective eye to provide eye feature scores.

The present invention relates to a method and apparatus of utilizing an eye detection apparatus in a medical application, which includes calibrating the eye detection apparatus to a user; performing a predetermined set of visual and cognitive steps using the eye detection apparatus; determining a visual profile of a workflow of the user; creating a user-specific database to create an automated visual display protocol of the workflow; storing eye-tracking commands for individual user navigation and computer interactions; storing context-specific medical application eye-tracking commands, in a database; performing the medical application using the eye-tracking commands; and storing eye-tracking data and results of an analysis of data from performance of the medical application, in the database. The method includes performing an analysis of the database for determining best practice guidelines based on clinical outcome measures.

Systems, methods, and processes are provided for locating pupils in a portrait image for applications such as facial recognition, facial authentication, and manufacture of identification documents. One proposed method comprises three steps; skin detection, eye detection, and pupil detection. In the first step, the skin detection employs a plurality of Gaussian skin models. In the second step, coarse eye locations are found by using the amount of deviation in the R (red) channel with an image that has been cropped by skin detection. A small block centered at an obtained coarse location is then further processed in pupil detection. The step of pupil detection involves determining a Pupil Index that measures the characteristics of a pupil. Experiments tested on highly jpeg compressed images show that the algorithm of this embodiment successfully locates pupil images. It is believed that this novel technique for locating pupils in images can improve the accuracy of face recognition and/or face authentication.

Eye detection is used as the basis for providing power management or other variations of operational parameters of a controlled device. The system includes an imager and eye detection processing which cooperate to detect light received from a person's eye. The eye detection processing generates an output that can be used for determinations regarding presence of one or more persons or presence of a specific person. This output is used as the basis for switching the controlled device between at least two power consumption states. Eye detection may also be used to allow a person to actively adjust operational conditions of the controlled device, since unnatural eye blinking patterns may be associated with particular commands.

To reduce degradation of recognition performance due to eye detection errors during face verification and to overcome a problem in that sufficient data to design an optimum feature classifier cannot be obtained during face registration, a method includes shifting the positions of eyes detected during face registration in predetermined directions by a predetermined distance to generate pairs of new coordinate points of the eyes; normalizing a face image on the basis of each pair of new coordinate points of the eyes; using the results of normalization in teaching a feature classifier, thereby coping with eye detection errors. In addition, two threshold values are used to prevent a database from being updated with a face of an unregistered person and to update the database with a normal client's face image that has been used during the latest face verification.

Alarm systems comprises an eye gaze direction detecting part, an obstacle detecting device and an alarm controlling part. The eye gaze direction detecting part determines a vehicle driver's field of view by analyzing facial images of a driver of the vehicle pictured by using a camera equipped in the vehicle. The obstacle detecting device detects the presence of an obstacle in the direction unobserved by the driver using a radar equipped in the vehicle, the direction of which radar is set up in the direction not attended by the driver on the basis of data detected by the eye gaze monitor. The alarm controlling part determines whether to make an alarm in case an obstacle is detected by the obstacle detecting device. The systems can detect the negligence of a vehicle driver in observing the front view targets and release an alarm to prevent the driver from any possible danger.

The present invention provides a fundus image classification method and device of retinopathy. The method comprises a step of obtaining the fundus image of an eye detection patient, a step of preprocessing the fundus image and obtaining a corresponding grey fundus image, a step of extracting a preset image characteristic in the grey fundus image, a step of analyzing the preset image characteristic according to the diabetic retinopathy classification model of the fundus image, and obtaining the classification result of the corresponding fundus image, a step of extracting the preset image characteristic in the preprocessed grey fundus image, and carrying out prediction classification on the above preset image characteristic through the diabetic retinopathy classification model established according to a support vector machine and a deep neural network so as to obtain a final classification result. The artificial participation is not needed in the whole process, the workload of doctors is reduced, the high standard requirement of the medical qualification level of the doctor is reduced, the accuracy of classification is improved, and the method and the device have great significance for specific applications and medical research.

A primarily hand-held or adjustable-mount iris recognition device wherein feedback to the operator is provided by visible illumination or imagery projected onto the face of the subject, as well as an audio signal, while infra-red illumination is projected onto the face of the subject as an illumination source for an iris recognition process. When the device is pointed in the direction of the subject, the infra-red illumination is directed to illuminate primarily the eye region whereas the visible illumination is directed to illuminate primarily other regions including the cheeks. The visible illumination is configured such that the position of the visible illumination on the face indicates to the operator whether the iris recognition device is pointed in the correct direction and at the correct distance for optimal iris recognition. The brightness of the visible illumination is modified in response to the result of an eye detection process performed on the iris recognition device, and the brightness, color and other attributes of the visible illumination or the audio signal are modified in response to the result of eye-finding or other process, including the results of an iris recognition process.

System and methods for non-intrusive real-time eye detection and tracking are disclosed. A subject's eyes can be detected by using active illumination analysis to generate a difference image of the subject. In the difference image, the bright pupil effect intensifies the appearance of the subject's pupils. A component analysis can be used to identify a set of pupil candidates from the difference image. An appearance-based analysis can be applied to the pupil candidates to identify the subject's eyes from background noise that can occur under various lighting conditions. After the subject's eyes are detected, a multi-stage tracking process is disclosed for detecting real-time eye movements. Further features are disclosed such as an image acquisition apparatus that reduces external illumination interferences.

A photographing apparatus including: an imaging unit for obtaining image data by imaging a subject; a light irradiation unit for irradiating light onto the subject when photographing; an eye detection unit for detecting a human or animal eye; and a light control unit for changing the irradiation condition of the light such that the light is irradiated on a position of the subject other than the eye detected by the eye detection unit.

The invention discloses a driving safety monitoring system based on face orientation and visual focus, which comprises a vision sensor and an intelligent processor. The intelligent processor comprises an image acquisition module, a complexion area detection module, an edge extraction module, an eye detection module, a face orientation analysis module and a driver safety driving judgment module, wherein the complexion area detection module is used for converting an RGB color space into a YCrCb color space and detecting a complexion area; the edge extraction module is used for adopting a Canny operator to carry out edge extraction so as to acquire a head image outline; the eye detection module is used for carrying out Hough conversion for the marginalized face and positioning eyes; the face orientation analysis module is used for determining a mouth area, positioning the mouth, calculating left and right areas of the face respectively by using the eyes and the mouth as reference, and calculating the ratio of the left and right areas of the face; and the driver safety driving judgment module is used for judging an unsafe driving state if the calculated ratio of the left and right areas of the current face is out of a preset interval according to the preset interval of the ratio of the left and right areas of the face, and sending out an alarm command. The driving safety monitoring system has strong capacity of resisting disturbance and high accuracy.

The invention generally relates to systems and methods for eye detection for use in, for example, installations and systems for tracking eyes and gaze angle/directions. The system includes a plurality of eye detection units connected to an image sensor. The eye detection units are adapted to receive regions of picture elements of a digital image frame substantially in parallel and wherein the eye detection units are adapted to operate substantially in parallel, each eye detection unit being adapted to receive a specified region of the picture elements of at least one digital image frame and including an eye feature extraction module adapted to perform a eye feature extraction process on the received picture elements to identify predetermined eye features. An eye data generating module is adapted to receive information of potential identified eye features including picture element coordinates for the identified eye features, and the received region of picture elements, and generate eye data based on the information of potential eye features, wherein the eye data is generated if identified eye features fulfil predetermined conditions, and transfer generated eye data and the received regions of picture elements to a processing module, and wherein a data flow of the eye data and the region of picture elements of a digital image frame is substantially parallel.

A display device for displaying pictures at different angles based on the visual angle of a viewer comprises a display screen, a camera and a computer control system, wherein the computer control system is prestored with a series of pictures or videos taken at different visual angles of the same scene. The display device is characterized in that the camera is started by using the computer controlsystem to photograph the viewer in front of the display screen, and then the image of the viewer is sent to the computer control system; a face candidate region is quickly located on the image of theviewer photographed by a computer using the camera by combining a motion analysis method and a skin analysis method, and then a human-eye detection algorithm is applied to detecting the position of the eyes of the viewer; by combining the distance from the viewer to a screen, the visual angle between the viewer and the camera is calculated according to a formula described in the specification, and the visual angle theta between the viewer and the display screen is approximately equal to the visual angle gamma between the viewer and the camera according to another formula under the condition that the distance from the non-large screen of the display screen to the viewer is more than 1 m; after receiving the information of the visual angles, the system outputs pictures or videos corresponding to the visual angles to the display screen; in the formulas, theta is the visual angle of the viewer, f is the focal length of the lens of the camera, d is the distance from a target point in the collected image to the central point of the image and gamma is the visual angle between the viewer and the camera, theta is the visual angle between the viewer and the display screen, l is half of the width of the display screen, d is the distance from the viewer to the display screen, and beta is a rotating angle between the viewer and the centre line of the display screen.

The invention provides chip appearance detection method and system, which is applicable to the technical field of chip appearance detection, wherein the method comprises the following steps of: obtaining a picture of a chip to be tested; identifying whether a welding disc exists on the picture of the chip to be tested or not; storing the position information of the welding disc when the existenceof the welding disc is identified, and carrying out primary gray processing on the obtained picture of the chip to be tested according to the stored position information of the welding disc; carryingout communicated region analysis on the picture of the chip to be tested after the first gray processing; and identifying whether defects exist on the welding disc or not. The automatic identification of appearance defect of the welding disc on the chip can be realized, and the problems of low detection speed and low detection efficiency caused by welding disc defect of the manual eye detection mode can be avoided. In addition, after the step of obtaining the picture of the chip to be tested and before identifying whether the welding disc exists on the picture of the chip to be tested or not according to the shape characteristic of the welding disc, whether the dimension of the chip to be tested is qualified or not can be judged through extracting the dimension data of the chip to be tested and comparing the obtained data to the stored chip dimension data.

The invention elates to a human face character position method in the field of image processing technology. It first uses human face detecting method to find the human face area in the image, and then it detects eyes of human face area to fide the location of two eyes, then it according to the middle location of the two eyes, the distance between the two eyes and the angle of the two eyes to do imitate-injecting transformation to the initial ASM module so that the initial location of ASM module is near to the module which is formed by real character points, at last it dose ASM searching to the initial location after imitate-injecting transformation so as to obtain the location of human face character point.

Redeye removal methods detect redeyes in a two-step procedure. In the first step it detects faces in the input image and in the second step it searches for redeyes in the detected faces. The methods include the introduction of an efficient skin tone detector that reduces the average complexity of a Viola-Jones based face. We also introduce a summed area table (SAT) based optimization in our eye detector stage that reduces the complexity in the eye detector by a factor of 5× when compared to an optimized direct search method.