In the cases of severe paralysis in which the ability to control the body movements of a person 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 communications often require special hardware or reliance on active infrared illumination. In this paper, we propose a non-intrusive algorithm for eye gaze estimation that works with video input from an inexpensive camera and without special lighting. The main contribution of this paper is proposing a new geometrical model for eye region that only requires the image of one iris for gaze estimation. Essential parameters for this system are the best fitted ellipse of the iris and the pupil center. The algorithms used for both iris ellipse fitting and pupil center localization pose no pre-assumptions on the head pose. All in all, the achievement of this paper is the robustness of the proposed system to the head pose variations. The performance of the method has been evaluated on both synthetic and real images leading to errors of 2.12 and 3.48 degrees, respectively. پرونده مقاله

In recent years, facial expression recognition, as an interesting problem in computer vision has been performed by means of static and dynamic methods. Dynamic information plays an important role in recognizing facial expression. However, using the entire dynamic information in the expression image sequences is of higher computational cost compared to the static methods. To reduce the computational cost, instead of entire image sequence, only neutral and emotional faces can be employed. In the previous research, this idea was used by means of DLBPHS method in which facial important small displacements were vanished by subtracting LBP features of neutral and emotional face images. In this paper, a novel approach is proposed to utilize two face images. In the proposed method, the face component displacements are highlighted by subtracting neutral image from emotional image; then, LBP features are extracted from the difference image. The proposed method is evaluated on standard databases and the results show a significant accuracy improvement compared to DLBPHS. پرونده مقاله