Human eye gaze is a strong candidate to create a new application area based on human-computer interaction. To implement a really practical gaze-based interaction system, gaze detection must be realized without placing any restriction on the user’s behavior or comfort. This paper describes a gaze tracking system that offers freehead, simple personal calibration. It does not require the user wear anything on her head, and she can move her head freely. Personal calibration takes only a very short time; the user is asked to look at two markers on the screen. An experiment shows that the accuracy of the implemented system is about 1.0 degrees (view angle).

Eye-gaze as a form of human machine interface holds great promise for improving the way we interact with machines. Eyegaze tracking devices that are non-contact, non-restrictive, accurate and easy to use will increase the appeal for including eye-gaze information in future applications. The system we have developed and which we describe in this paper achieves these goals using a single high resolution camera with a fixed field of view. The single camera system has no moving parts which results in rapid reacquisition of the eye after loss of tracking. Free head motion is achieved using multiple glints and 3D modeling techniques. Accuracies of under 1 ° of visual angle are achieved over a field of view of 14x12x20 cm and over various hardware configurations, camera resolutions and frame rates.

Abstract—Despite active research and significant progress in the last 30 years, eye detection and tracking remains challenging due to the individuality of eyes, occlusion, variability in scale, location, and light conditions. Data on eye location and details of eye movements have numerous applications and are essential in face detection, biometric identification, and particular human-computer interaction tasks. This paper reviews current progress and state of the art in video-based eye detection and tracking in order to identify promising techniques as well as issues to be further addressed. We present a detailed review of recent eye models and techniques for eye detection and tracking. We also survey methods for gaze estimation and compare them based on their geometric properties and reported accuracies. This review shows that, despite their apparent simplicity, the development of a general eye detection technique involves addressing many challenges, requires further theoretical developments, and is consequently of interest to many other domains problems in computer vision and beyond. Index Terms—Eye, eye detection, eye tracking, gaze estimation, review paper, gaze tracking, object detection and tracking, human-computer interaction. Ç 1

Many eye-tracking systems either require the user to keep their head still or involve cameras or other equipment mounted on the user’s head. While acceptable for research applications, these limitations make the systems unsatisfactory for prolonged use in interactive applications. Since the goal of our work is to use eye

Abstract—In the cases of paralysis so severe that a person’s ability to control movement is limited to the muscles around the eyes, eye movements or blinks are the only way for the person to communicate. Interfaces that assist in such communication are often intrusive, require special hardware, or rely on active infrared illumination. A nonintrusive communication interface system called EyeKeys was therefore developed, which runs on a consumer-grade computer with video input from an inexpensive Universal Serial Bus camera and works without special lighting. The system detects and tracks the person’s face using multiscale template correlation. The symmetry between left and right eyes is exploited to detect if the person is looking at the camera or to the left or right side. The detected eye direction can then be used to control applications such as spelling programs or games. The game “BlockEscape ” was developed to evaluate the performance of EyeKeys and compare it to a mouse substitution interface. Experiments with EyeKeys have shown that it is an easily used computer input and control device for able-bodied people and has the potential to become a practical tool for people with severe paralysis. Index Terms—Assistive technology, disabled computer users, face detection, face tracking, gaze estimation, video-based human–computer interfaces, webcams. I.

Abstract—Most available remote eye gaze trackers have two characteristics that hinder them being widely used as the important computer input devices for human computer interaction. First, they have to be calibrated for each user individually; second, they have low tolerance for head movement and require the users to hold their heads unnaturally still. In this paper, by exploiting the eye anatomy, we propose two novel solutions to allow natural head movement and minimize the calibration procedure to only one time for a new individual. The first technique is proposed to estimate the 3-D eye gaze directly. In this technique, the cornea of the eyeball is modeled as a convex mirror. Via the properties of convex mirror, a simple method is proposed to estimate the 3-D optic axis of the eye. The visual axis, which is the true 3-D gaze direction of the user, can be determined subsequently after knowing the angle deviation between the visual axis and optic axis by a simple calibration procedure. Therefore, the gaze point on an object in the scene can be obtained by simply intersecting the estimated 3-D gaze direction with the object. Different from the first technique, our second technique does not need to estimate the 3-D eye gaze directly, and the gaze point on an object is estimated from a gaze mapping function implicitly. In addition, a dynamic computational head compensation model is developed to automatically update the gaze mapping function whenever the head moves. Hence, the eye gaze can be estimated under natural head movement. Furthermore, it minimizes the calibration procedure to only one time for a new individual. The advantage of the proposed techniques over the current state of the art eye gaze trackers is that it can estimate the eye gaze of the user accurately under natural head movement, without need to perform the gaze calibration every time before using it. Our proposed methods will improve the usability of the eye gaze tracking technology, and we believe that it represents an important step for the eye tracker to be accepted as a natural computer input device. Index Terms—Eye gaze tracking, gaze estimation, human computer interaction. I.

A single camera iris tracking and remapping approach based on passive computer vision is presented. Tracking is aimed at obtaining accurate and robust measurements of the iris/pupil position. To this purpose, a robust method for ellipse fitting is used, employing search constraints so as to achieve a better performance with respect to the standard RANSAC algorithm. Tracking also embeds an iris localization algorithm (working as a bootstrap multiple-hypotheses generation step), and a blink detector, that can detect voluntary eye blinks in human-computer interaction applications. On-screen remapping incorporates a head tracking method capable of compensating for small user head movements. The approach operates in real time under different light conditions and in the presence of distractors. An extensive set of experiments is presented and discussed. In particular, an evaluation method for the choice of the layout of both hardware components and calibration points is described. Experiments also investigate the importance of providing a visual feedback to the user, and the benefits gained from performing head compensation, especially during image-to-screen map calibration.

Abstract—A bioptic telescope is a visual aid used by people with impaired vision when driving in many U.S. states, though bioptic driving remains controversial. Objective data on how and when bioptic drivers use the telescope and what they look at with it are crucial to understanding the bioptic telescope’s effects on driving. A video-based technique to track the telescope’s aiming point is presented in this paper. With three infrared retro-reflective markers pasted on the bioptic spectacles frame, its movement is recorded using an infrared camera unit with infrared LED illuminators. The angles formed by the three markers are used to calculate the telescope’s aiming points, which are registered with road scene images recorded by another camera. The calculation is based on a novel one-time calibration method, in which the light spot from a head-mounted laser pointer projected on a wall while the scanning is recorded by the scene camera, in synchronization with the infrared camera. Interpolation is performed within small local regions where no samples were taken. Thus, nonlinear interpolation error can be minimized, even for wide-range tracking. Experiments demonstrated that the average error over a 70 48 field was only 0.86, with lateral head movement allowed. Index Terms—Bioptic driving, head tracking, instrumented vehicle, low vision, vision rehabilitation. I.

Abstract. The purpose of this study is to develop an appearance-based method for estimating gaze directions from low resolution images. The problem of estimating directions using low resolution images is that the position of an eye region cannot be determined accurately. In this work, we introduce two key ideas to cope with the problem: incorporating training images of eye regions with artificially added positioning errors, and separating the factor of gaze variation from that of positioning error based on Æ-mode SVD (Singular Value Decomposition). We show that estimation of gaze direction in this framework is formulated as a bilinear problem that is then solved by alternatively minimizing a bilinear cost function with respect to gaze direction and position of the eye region. In this paper, we describe the details of our proposed method and show experimental results that demonstrate the merits of our method. Key words: gaze estimation, low resolution, appearance-based method, positioning, Æ-mode SVD 1

Abstract. User attention recognition in front of a monitor or a specific task is a crucial issue in many applications, ranging from e-learning to driving. Visual input is very important when extracting information regarding a user’s attention when recorded with a camera. However, intrusive equipment (special helmets, glasses equipped with cameras recording the eye movements, etc.) impose constraints on users spontaneity, especially when the target group consists of under aged users. In this paper, we propose a system for inferring user attention (state) in front of a computer monitor, only with the usage of a simple camera. The system can be used for real time applications and does not need calibration in terms of camera parameters. It can function under normal lighting conditions and needs no adaptation for each user.