Delphi Technologies, Inc.

Riad I Hammoud

Matthew R Smith

Phillip V Malawey

Andrew L Wilhelm

Gerald J Witt

Harry Zhang

Andrew P Harbach

Phillip V Malaway

A system and method are provided for determining eye closure state of the eye of a subject. The system includes a video imaging camera oriented to generate images of an eye of a subject and a video processor for processing the images generated with the video imaging camera. The video processor is configured to detect an eye in the video images and determine whether the images of the eye are noisy. The video processor processes geometrical and statistical shape of the eye in the images if the eye is not noisy, and processes changes in the size of the eye over time if the images are noisy. The processor further determines eye closure state based on a ratio of horizontal to vertical dimensions.

Eye closure recognition system and method

An awareness detection system and method are provided. The system includes an imaging device positioned to obtain a plurality of images of at least a portion of a subject's head, and an awareness processor in communication with the imaging device. The awareness processor receives an image from the imaging device and performs the steps including conducting a two-point head pose analysis when two eyes of the subject are located, conducting a one-point head pose analysis when only one eye of the subject is located, and conducting a zero-point head pose analysis when zero eyes of the subject are located. The awareness processor further performs the steps of detecting at least one point of interest in the image, conducting a motion analysis of the image to estimate a head pose of the subject, and determining a state of awareness of the subject.

System and method of awareness detection

A system and method are provided for monitoring an eye to determine eye closure. The system includes a video imaging camera oriented to generate images of an eye, and a video processor for processing the images. The processor includes an edge detector for detecting edges of the eye in the image, and a line selector for generating lines at any of select angles representative of the detected edges. The processor determines the state of eye closure, such as an open eye or closed eye, based on an angle between two of the lines that select angles. The system may be employed on a vehicle to determine the eye closure state of a driver of the vehicle.

System and method of detecting eye closure based on line angles

A dynamic eye tracking system to track movement of an eye including the steps of detecting if a neighbor exists about the eye over a predetermined amount of time and forming a boundary for the neighbor. Eye candidates are tracked and a determination is made if the eye candidates are beyond the boundary defined by the detected neighbor.

Dynamic eye tracking system

A system for measuring the awareness of a subject including an imaging device adapted to acquire data representative of an image of the subject, and an awareness processor connected to the imaging device, wherein the awareness processor is adapted to classify the awareness of the subject according to the position of the subject.

System and method to determine awareness

A system and method are provided for detecting one or both eyes of the driver of a vehicle. The system includes a video imaging camera oriented to generate images of the driver's face. The system also includes a video processor for processing the images generated with the video imaging camera. Filters are applied to each of potential eye candidates to determine which candidates represent an eye, weighted values are assigned to the filtered eye candidates, and an eye is detected based on the weighting of each eye candidate. According to one aspect, different size patches of potential eye candidates are processed and compared to models.

System and method for detecting an eye

A human eye is detected in a video image by identifying potential eye candidates using horizontal and vertical projection filtering on a specified portion of the image, coupled with rudimentary appearance-based testing. The identified eye candidates are clustered and winning eye candidates are selected based on appearance, spatial-geometric and anthropomorphic considerations. The winning eye candidates are subjected to additional appearance-based testing, and high confidence eye candidates are accepted if they favorably compare with identified eye candidates from previous video image frames.

Method of locating a human eye in a video image

A human eye is tracked between successively produced video image frames by consecutively applied eye location techniques. First, potential eye candidates within a local search window are identified using horizontal projection filtering, coupled with rudimentary appearance-based testing. The identified eye candidates are clustered and subjected to additional appearance-based testing to determine if one or more eye candidates should be accepted. If no eye candidates are accepted, a correlation/appearance technique is applied to the search window to identify the eye. If unsuccessful, the eye may be closed, and peripheral eye-related patches from the previous image frame are extracted and compared with the search window to identify the eye in the current frame. When comparable eye-related patches are identified in the search window for the current frame, the eye center is computed according to the mean of the eye periphery patches.

Method of tracking a human eye in a video image

The face of a human subject is alternately illuminated by first and second sources of active illumination disposed above and below a video camera that captures images of the subject's face. Glare due to reflection of the active illumination from eyeglasses worn by the subject shifts up or down from one image to the next due to the different locations of the first and second sources. Eye detection and tracking routines ignore images in which the eye is occluded by eyeglass glare so that the glare does not interfere with the performance of the routines.

Eye monitoring method with glare spot shifting

The presence of eyeglasses worn by a human subject is detected regardless of whether the subject's head is viewed frontally or in profile. Image data within search windows defined relative to the subject's eye is processed to form linear representations of edge boundaries. Angles formed by intersections of the linear representations are determined and used as a basis for determining if eyeglass lenses are present. When prescribed eyeglass components are detected, the eye detection and tracking routines are configured accordingly.

Eyeglass detection method

An object tracking method tracks a target object between successively generated infrared video images using a grey-scale hat filter to extract the target object from the background. The filtered image is binarized, and candidate binary blobs are extracted. The binary blob that minimizes the Euclidian spatial distance to the previous position of the object and satisfies a specified appearance model is selected, and its center of mass is taken as the current position of the object. Where the object is a person's eye, the eye state and decision confidence are determined by analyzing the shape and appearance of the binary blob along with changes in its size and the previous eye state, and applying corresponding parameters to an eye state decision matrix.

Object tracking and eye state identification method

An eye tracking method tracks a subject's eye template by correlation between successive video frames, and periodically updates the eye template based on detected characteristic eye or eyelid movement such as blinking, eyelash movement and iris movement. In the absence of eyelid motion detection, a state vector corresponding to the center of the subject's eye is determined by a correlation technique, and when eyelid motion is detected, the state vector is determined based on the location of the detected motion.

Eye tracking method based on correlation and detected eye movement

A system and method are provided for monitoring an eye to determine eye closure. The system includes a video imaging camera oriented to generate images of an eye. The system also includes a video processor for processing the images generated with the video imaging camera. The processor includes an edge detector for detecting edges of the eye in the image and a line selector for generating substantially horizontal first and second lines representative of the detected edges. The processor determines the state of eye closure, such as eye open or eye closed, based on distance between the first and second lines. The system may be employed on a vehicle to determine the eye closure of a driver of the vehicle.

System and method for determining eye closure state

A system and method are provided for monitoring an eye to determine eye closure. The system includes a video imaging camera oriented to generate images of an eye, and a video processor for processing the images. The processor includes an edge detector for detecting edges of the eye in the image, and a line selector for generating a plurality of lines at multiple angles representative of the detected edges. The processor determines the state of eye closure, such as eye open or eye closed, based on the number of lines at selected angles. The system may be employed on a vehicle to determine the eye closure of a driver of the vehicle.

Growing community of inventors

Kokomo, IN, United States of America

Riad I Hammoud