Search Results (4)

Recently, many studies have actively dealt with the issue of driver-gaze tracking for monitoring the forward gaze and physical condition. Driver-gaze tracking is an effective method of measuring a driver’s inattention that is one of the major causes of traffic accidents. Among many gaze-tracking methods, the corneal specular reflection (SR)-based method becomes ineffective, unlike in an indoor environment, when a driver’s head rotates, which makes SR disappear from input images or disperses SR in the lachrymal gland or eyelid, thereby increasing the gaze-tracking error. Besides, since a driver’s eyes in a vehicle environment need to be captured in a wide range covering his head rotation, the eye region is captured in a relatively low resolution compared to face-only images taken in indoor environments at the same resolution, making pupil and corneal SR difficult to detect accurately. To solve these problems, we propose a fuzzy-system-based method for detecting a driver’s pupil and corneal SR for gaze tracking in a vehicle environment. Unlike existing studies detecting pupil and corneal SR in both eyes, the method proposed in this research uses the results of a fuzzy system based on two features considering the symmetrical characteristics of face and facial feature points to determine the status of a driver’s head rotation. Based on the output of the fuzzy system, the proposed method excludes the eye region, which is very likely to have a high error rate of detection due to excessive head rotation, from the detection process of the pupil and corneal SR. Accordingly, the proposed method detects pupil and corneal SR only in the eye region that apparently has a low detection error rate, thereby achieving accurate detection. We use 20,654 images capturing 15 subjects (including subjects wearing glasses), who gaze at pre-set fifteen regions in a vehicle, to measure the detection accuracy of the pupil and corneal SR for each region and the gaze tracking accuracy. Our experimental results show that the proposed method performs better than existing methods. Full article

Most gaze tracking systems are based on the pupil center corneal reflection (PCCR) method using near infrared (NIR) illuminators. One advantage of the PCCR method is the high accuracy it achieves in gaze tracking because it compensates for the pupil center position based on the relative position of corneal specular reflection (SR). However, the PCCR method only works for user head movements within a limited range, and its performance is degraded by the natural movement of the user’s head. To overcome this problem, we propose a gaze tracking method using an ultrasonic sensor that is robust to the natural head movement of users. Experimental results demonstrate that with our compensation method the gaze tracking system is more robust to natural head movements compared to other systems without our method and commercial systems. Full article

Gaze tracking systems usually utilize near-infrared (NIR) lights and NIR cameras, and the performance of such systems is mainly affected by external light sources that include NIR components. This is ascribed to the production of additional (imposter) corneal specular reflection (SR) caused by the external light, which makes it difficult to discriminate between the correct SR as caused by the NIR illuminator of the gaze tracking system and the imposter SR. To overcome this problem, a new method is proposed for determining the correct SR in the presence of external light based on the relationship between the corneal SR and the pupil movable area with the relative position of the pupil and the corneal SR. The experimental results showed that the proposed method makes the gaze tracking system robust to the existence of external light. Full article

Conventional gaze tracking systems are limited in cases where the user is wearing glasses because the glasses usually produce noise due to reflections caused by the gaze tracker’s lights. This makes it difficult to locate the pupil and the specular reflections (SRs) from the cornea of the user’s eye. These difficulties increase the likelihood of gaze detection errors because the gaze position is estimated based on the location of the pupil center and the positions of the corneal SRs. In order to overcome these problems, we propose a new gaze tracking method that can be used by subjects who are wearing glasses. Our research is novel in the following four ways: first, we construct a new control device for the illuminator, which includes four illuminators that are positioned at the four corners of a monitor. Second, our system automatically determines whether a user is wearing glasses or not in the initial stage by counting the number of white pixels in an image that is captured using the low exposure setting on the camera. Third, if it is determined that the user is wearing glasses, the four illuminators are turned on and off sequentially in order to obtain an image that has a minimal amount of noise due to reflections from the glasses. As a result, it is possible to avoid the reflections and accurately locate the pupil center and the positions of the four corneal SRs. Fourth, by turning off one of the four illuminators, only three corneal SRs exist in the captured image. Since the proposed gaze detection method requires four corneal SRs for calculating the gaze position, the unseen SR position is estimated based on the parallelogram shape that is defined by the three SR positions and the gaze position is calculated. Experimental results showed that the average gaze detection error with 20 persons was about 0.70° and the processing time is 63.72 ms per each frame. Full article