Unobtrusive and pervasive video-based eye-gaze tracking

Eye-gaze tracking has long been considered a desktop technology that finds its use inside the traditional office setting, where the operating conditions may be controlled. Nonetheless, recent advancements in mobile technology and a growing interest in capturing natural human behaviour have motivated an emerging interest in tracking eye movements within unconstrained real-life conditions, referred to as pervasive eye-gaze tracking. This critical review focuses on emerging passive and unobtrusive video-based eye-gaze tracking methods in recent literature, with the aim to identify different research avenues that are being followed in response to the challenges of pervasive eye-gaze tracking. Different eye-gaze tracking approaches are discussed in order to bring out their strengths and weaknesses, and to identify any limitations, within the context of pervasive eye-gaze tracking, that have yet to be considered by the computer vision community.peer-reviewe

Highly accurate and fully automatic 3D head pose estimation and eye gaze estimation using RGB-D sensors and 3D morphable models

The research presented in the paper was funded by grant F506-FSA of the Auto21 Networks of Centers of Excellence Program of Canada.This work addresses the problem of automatic head pose estimation and its application in 3D gaze estimation using low quality RGB-D sensors without any subject cooperation or manual intervention. The previous works on 3D head pose estimation using RGB-D sensors require either an offline step for supervised learning or 3D head model construction, which may require manual intervention or subject cooperation for complete head model reconstruction. In this paper, we propose a 3D pose estimator based on low quality depth data, which is not limited by any of the aforementioned steps. Instead, the proposed technique relies on modeling the subject's face in 3D rather than the complete head, which, in turn, relaxes all of the constraints in the previous works. The proposed method is robust, highly accurate and fully automatic. Moreover, it does not need any offline step. Unlike some of the previous works, the method only uses depth data for pose estimation. The experimental results on the Biwi head pose database confirm the efficiency of our algorithm in handling large pose variations and partial occlusion. We also evaluated the performance of our algorithm on IDIAP database for 3D head pose and eye gaze estimation.Publisher PDFPeer reviewe

Low Cost Eye Tracking: The Current Panorama

Despite the availability of accurate, commercial gaze tracker devices working with infrared (IR) technology, visible light gaze tracking constitutes an interesting alternative by allowing scalability and removing hardware requirements. Over the last years, this field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration strategies, head pose invariance, and gaze estimation techniques. We also provide information on related aspects of research such as public datasets to test against, open source projects to build upon, and gaze tracking services to directly use in applications. With all this information, we aim to provide the contemporary and future researchers with a map detailing previously explored ideas and the required tools

Low Cost Eye Tracking : The Current Panorama

Altres ajuts: Consolider 2010 MIPRCV, Universitat Autonoma de Barcelona i Google Faculty AwardDespite the availability of accurate, commercial gaze tracker devices working with infrared (IR) technology, visible light gaze tracking constitutes an interesting alternative by allowing scalability and removing hardware requirements. Over the last years, this field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration strategies, head pose invariance, and gaze estimation techniques. We also provide information on related aspects of research such as public datasets to test against, open source projects to build upon, and gaze tracking services to directly use in applications. With all this information, we aim to provide the contemporary and future researchers with a map detailing previously explored ideas and the required tools

Detección del punto de observación de un usuario sobre una pantalla mediante una webcam

La motivación principal de este trabajo ha sido investigar e implementar un método para estimar el punto de observación de un usuario en una pantalla con la mayor precisión posible, usando sólo la webcam que disponga el ordenador o tablet del usuario. Recientes estudios han investigado la interacción del usuario con las máquinas usando la mirada, surgiendo así soluciones para métodos de comunicación de personas discapacitadas, nuevas formas de controlar el ratón y el teclado, o incluso nuevos métodos de aprendizaje, como, por ejemplo, podría seguirse la mirada mientras un niño realiza sus primeras lecturas, o conocer que estímulos llaman más la atención en juegos educativos. Los métodos actuales de seguimiento de la mirada utilizan iluminación infrarroja, cámaras de alta calidad de vídeo, y requieren una posición relativa estable entre el ojo del usuario y la cámara. Pero estas cámaras son caras y no son viables para los dispositivos cotidianos. Éstos deben lidiar con recursos computacionales limitados, baja resolución de imágenes usando la webcam frontal integrada, condiciones adversas de luz, tamaños pequeños de pantalla donde mapear la mirada o movimientos de la cabeza del usuario. Después de la investigación del estado del arte, se ha propuesto e implementado una posible solución con la que se ha tenido que tener en cuentas una serie de aspectos previos. Estos aspectos previos han sido encontrar una serie de puntos característicos en la imagen del usuario, que serán necesarios para estimar el punto de observación mediante la solución propuesta. La evaluación del funcionamiento y del cumplimiento de unos requisitos previos se realizará mediante voluntarios a quienes se les ha sometido a una serie de pruebas. Se ha tenido en cuenta la precisión a la hora de estimar el punto de observación tanto del eje horizontal como del vertical, implementándose dos métodos para evaluar éste último, entre los cuales se realizará una comparativa. Con todo lo anteriormente expuesto, se han extraído una serie de conclusiones.The main motivation behind this work has been to investigate and implement a method of estimating the gaze of a user with the possible precision. The camera have to be the computer webcam. There are many current studies on the interaction between machines and the user's gaze, for example, communication methods of disabled people, new ways of controlling the mouse and the keyboard or even new learning methods: follow the look of a child learning to read or know what stimuli call more attention in educational games. Current methods for gaze tracking use infrared illumination, high-quality video cameras, and require a stable relative position between the user's eye and the camera. However, in normal devices there are many limitations. In this work, a possible solution has been proposed and implemented. This solution need to find a series of characteristic points in the user's image, this will be the first step. The evaluation of the correct work of some prerequisites will be through volunteers who will undergo a series of tests. These tests will calculate the accuracy in the gaze localization in the horizontal and vertical axis. There are two methods to evaluate the vertical axis and a comparison will be made between both, and the appropriate conclusions have been drawn

Gaze Estimation from Low Resolution Images

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