We present a human point of gaze estimation system using corneal surface reflection and omnidirectional image taken by spherical panorama cameras, which becomes popular recent years. Our system enables to find where a user is looking at only from an eye image in a 360° surrounding scene image, thus, does not need gaze mapping from partial scene images to a whole scene image that are necessary in conventional eye gaze tracking system. We first generate multiple perspective scene images from an omnidirectional (equirectangular) image and perform registration between the corneal reflection and perspective images using a corneal reflection-scene image registration technique. We then compute the point of gaze using a corneal imaging technique leveraged by a 3D eye model, and project the point to an omnidirectional image. The 3D eye pose is estimate by using the particle-filter-based tracking algorithm. In experiments, we evaluated the accuracy of the 3D eye pose estimation, robustness of registration and accuracy of PoG estimations using two indoor and five outdoor scenes, and found that gaze mapping error was 5.546 [deg] on average.

The aim of this study is to present electrooculogram signals that can be used for human computer interface efficiently. Establishing an efficient alternative channel for communication without overt speech and hand movements is important to increase the quality of life for patients suffering from Amyotrophic Lateral Sclerosis or other illnesses that prevent correct limb and facial muscular responses. In this paper, we introduce the gaze estimation system of electrooculogram signals. Using this system, the electrooculogram signals can be recorded when the patients focused on each direct. All these recorded signals could be analyzed using math-method and the mathematical model will be set up. Gaze estimation can be recognized using electrooculogram signals follow these models.

We have proposed a novel geometric model of the eye in order to avoid the problems faced while using the conventional spherical model of the cornea for three dimensional (3D) model-based gaze estimation. The proposed model models the eye, including the boundary region of the cornea, as a general surface of revolution about the optical axis of the eye. Furthermore, a method for calculating the point of gaze (POG) on the basis of our model has been proposed. A prototype system for estimating the POG was developed using this method. The average root mean square errors (RMSEs) of the proposed method were experimentally found to be smaller than those of the gaze estimation method that is based on a spherical model of the cornea.