Pupil detection and tracking using multiple light sources

Morimoto, Carlos H.; Koons, David B.; Amir, Arnon; Flickner, Myron

doi:10.1016/s0262-8856(99)00053-0

Cited by 323 publications

(144 citation statements)

References 19 publications

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“…In this condition, a dark pupil image was obtained by using the NIR camera. When the NIR LED was installed close to the optical axis and was switched on, the IR LED light was reflected in the cornea, and thus, the pupil appeared very bright [28]. Another research used the circular Hough transform (HT) to detect pupil edges from eye images and then to detect circles with an equivalent radius from a center.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy-System-Based Detection of Pupil Center and Corneal Specular Reflection for a Driver-Gaze Tracking System Based on the Symmetrical Characteristics of Face and Facial Feature Points

Lee¹,

Yoon²,

Hong³

et al. 2017

Symmetry

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Abstract: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.

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Section: Related Workmentioning

confidence: 99%

Fuzzy-System-Based Detection of Pupil Center and Corneal Specular Reflection for a Driver-Gaze Tracking System Based on the Symmetrical Characteristics of Face and Facial Feature Points

Lee¹,

Yoon²,

Hong³

et al. 2017

Symmetry

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show abstract

“…An effective and robust technique is based on the corneal reflection, that is the reflection of the light on the surface of the cornea (Eizenman et al, 1984;Morimoto et al, 2000). Since the corneal reflection is the brightest reflection, its detection is simple, and offers a stable reference point for the gaze estimation.…”

Section: • Corneal Reflectionmentioning

confidence: 99%

“…In fact, the illuminators produce visible corneal reflexes, that are used as reference feature in other kinds of eye trackers (Eizenman et al, 1984;Morimoto et al, 2000). In our case, since we are seeking to use the limbus position to track the eye, if the reflex, depending on the position of the eye falls in its correspondence, it can lead to the detection of a wrong edge, thus to a wrong gaze estimation.…”

Section: Hardware Implementationmentioning

confidence: 99%

The Perspective Geometry of the Eye: Toward Image-Based Eye-Tracking

Canessa¹,

Gibaldi²,

Chessa³

et al. 2012

Human-Centric Machine Vision

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“…The eye detection is also very important for face detection, face recognition and facial expression analysis, which will be widely applied in the near future. The existing methods in eye detection can be classified into three types: the traditional image-based passive approaches [14][15][16][17][18], the mixed approaches [9][10][11][12][13], and the IR based active approaches [1][2][3][4][5][6][7][8].…”

Section: Introduction and Related Workmentioning

confidence: 99%

An Effective Method and Device for Eye Detection with Physical Properties

Quan¹,

Zhao²,

Li³

et al. 2013

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

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Abstract-Accurate detection of eyes plays an important role in human-machine interfaces. In this paper, according to some physical characteristics, a new designed device for the new real-time and effective eye detection method is proposed. In this device, two physical characteristics are applied, they are the Red-eye effect and the 850-property observed in the experiments. The detecting approach includes four steps, pretreating, matching by SURF (Speeded Up Robust Features), finding the difference and getting the points of the eyes. After these four steps, the positions of the eyes are obtained, and whether eye exists in the picture or not could also be judged. To speed up the detection, the matching parameters are recorded and adjusted periodically.

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Pupil detection and tracking using multiple light sources

Cited by 323 publications

References 19 publications

Fuzzy-System-Based Detection of Pupil Center and Corneal Specular Reflection for a Driver-Gaze Tracking System Based on the Symmetrical Characteristics of Face and Facial Feature Points

Fuzzy-System-Based Detection of Pupil Center and Corneal Specular Reflection for a Driver-Gaze Tracking System Based on the Symmetrical Characteristics of Face and Facial Feature Points

The Perspective Geometry of the Eye: Toward Image-Based Eye-Tracking

An Effective Method and Device for Eye Detection with Physical Properties

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