LiveMask

We present a telepresence system with a reduced scale face-shaped display for supporting intimate telecommunication. In our previous work, we have developed a real-size face shaped display that tracks and reproduces the remote user's head motion and face image. It can convey user's nonverbal information such as facial expression and gaze awareness. In this paper, we examine the value and effect of scale reduction of such face-shaped displays. We expect small size face displays retain the benefit of real-size talking-head type telecommunication systems, and also provide more intimate impression. It is easier to transport or put on a desk, and it can be worn on the shoulder of the local participants so that people bring it like a small buddy. However, it is not clear how such reduced-size face screen might change the quality of nonverbal communication. We thus conducted an experiment using a 1/14 scale face display, and found critical nonverbal information, such as gaze-direction, is still correctly transmitted even when face size is reduced.

This paper presents a novel three-dimensional (3-D) eye movement analysis algorithm for binocular eye tracking within virtual reality (VR). The user's gaze direction, head position, and orientation are tracked in order to allow recording of the user's fixations within the environment. Although the linear signal analysis approach is itself not new, its application to eye movement analysis in three dimensions advances traditional two-dimensional approaches, since it takes into account the six degrees of freedom of head movements and is resolution independent. Results indicate that the 3-D eye movement analysis algorithm can successfully be used for analysis of visual process measures in VR. Process measures not only can corroborate performance measures, but also can lead to discoveries of the reasons for performance improvements. In particular, analysis of users' eye movements in VR can potentially lead to further insights into the underlying cognitive processes of VR subjects.

In this paper, we propose a system that presents correct gaze directions of each user in a group-to-group video conference. It is known that gaze direction plays a significant role in face-to-face communication. However, in ordinary video conference systems, there is a problem that gaze directions cannot be correctly transmitted to a user in the other side since the camera is placed on the top or bottom of the display. We propose a method to generate images of each person from an appropriate viewpoint position using Kinect and screen-embedded cameras and to present the images to the user. By estimating each user's gaze direction and rendering the image of the person who the user is looking at from the users' viewpoint position, it is possible to present an image suitable for each user even in a group-to-group situation. We show demonstration of a group-to-group video conference using the proposed system and show that the system can present images suitable for each user.

In this paper, we suggest a new system to estimate the direction of a user's eye gaze. Our system consisted of five IR LEDs and a CCD camera. The IR LEDs, which are attached to the corners of a computer monitor, make glints on the surface of the cornea of the eye. If the user sees the monitor, the center of a pupil is always in a polygon that is made by the glints. Consequently, the direction of the user's eye gaze can be computed without computing the geometrical relation between the eye, the camera and the monitor in 3D space. Our method is comparatively simple and fast. We introduce the method and show some experimental results.

This paper describes the development of a binocular eye tracking Virtual Reality system for aircraft inspection training. The aesthetic appearance of the environment is driven by standard graphical techniques augmented by realistic texture maps of the physical environment. A "virtual flashlight" is provided to simulate a tool used by inspectors. The user's gaze direction, as well as head position and orientation, are tracked to allow recording of the user's gaze locations within the environment. These gaze locations, or scanpaths, are calculated as gaze/polygon intersections, enabling comparison of fixated points with stored locations of artificially generated defects located in the environment interior. Recorded scanpaths provide a means of comparison of the performance of experts to novices, thereby gauging the effects of training.

The LDA-based face recognition using face images by actual distance as training images showed good performance. However, it causes user inconvenience as it requires the user to move multiple distance in person to acquire face images for initial user registration. In this paper, LDA-based face recognition applicable to robotic environments is proposed. The proposed method can get face images by distance by zooming in on face of users without their cooperation and use those images for training. The experimental results show that the face recognition performance of the proposed method was as good as that of the method using face images by distance, which are taken after users are located at fixed positions within a fixed distance, for training.

This paper discusses the problem of gaze tracking and its applications to multimodal human-computer interaction. The function of a gaze tracking system can be either passive or active. For example, a system can identify user's message target by monitoring the user's gaze, or the user could use his gaze to directly control an application or launch actions. We have developed a real-time gaze tracking system that estimates the 3D position and rotation (pose) of a user's head. We demonstrate the applications of the gaze tracker to human-computer interaction by two examples. The first example shows that gaze tracker can help speech recognition systems by switching language model and grammar based on user's gaze information. The second example illustrates the combination of the gaze tracker and a speech recognizer to view a panorama image.

Recently, some novel human-machine interfaces (HMI) have been created for disabled and elderly people to control intelligent wheelchairs (IW) using facial and head gestures. To operate a wheelchair in this new visual-based control mode, user identification should be conducted beforehand. Rather than traditional user identification that requires the user to input his/her username and password by typing, the state-of-the-art biometric-based user identification provides a more convenient way for the disabled users. This paper first elaborates active shape model in details; then, video-based user identification using Mahalanobis distance is presented. As an extension, an adaptive learning module is designed to append or update the user's face record in the constructed face database. Experimental results show that our login subsystem is able to function well for a comparatively small face database.

Numerous cyber threats may succeed in cloud platforms owing to unproductive authentication methods. Multiple credential authentication is a vital precautionary measure that helps reinforce cloud security for warding off imminent data breaches and illegal access. This kind of authentication approach strongly guarantees that trustworthy clients are only ratified to get cloud services, making it less tiresome for clients and more secure for organizations. This study proposes an Image Forensics-based Dual Credential Authentication (IF-DCA) based on username (i.e., preferably email ID to avoid replica) and client photographs as password. Along with a username, a rapid and acquainted user action of capturing a photograph using a web camera is adequate for this method; hence it does not need any expensive, special hardware devices. During the registration phase, along with the username, the user's face image is stored on the cloud server as a password. When registered clients need to access cloud resources or data, they should log in on the server with their username and their photograph. To improve the authentication approach, this work proposes an Attribute-controlled Conditional Generative Adversarial Network (ACC-GAN) to generate face images of the same user at various age groups. ACC-GAN includes an additional attribute control unit and an age prediction unit to synthesize photo-realistic face images with aging effects. After matching the username and face image with the registered username and ACC-GAN-generated images, the face identification module provides access to the authorized cloud user. The performance of IF-DCA is assessed through the Cross-Age Celebrity Dataset using the MATLAB R2018b/deep learning toolbox. The empirical analysis reveals that the ACC-GAN achieves better performance measures such as 98.40% accuracy, 99.3% sensitivity, 90.0% specificity, and 95.7% precision. The performance of IF-DCA is analyzed using the verification time for username, user image, and complete authentication against the number of users. Received: 4 September 2024 | Revised: 14 October 2024 | Accepted: 7 November 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The Cross-Age Celebrity Datasets that support the findings of this study are openly available at https://paperswithcode.com/dataset/cacd. Author Contribution Statement Pranali Dahiwal: Conceptualization, Software, Formal analysis, Resources, Writing – original draft, Visualization, Project administration. Vijay Khare: Methodology, Validation, Investigation, Data curation, Writing – review & editing, Supervision.

We propose a novel method of tracking the gaze direction of human eyes using a neural network (NN). First, ten primary parameters are extracted from the image of a human face by using the mountain algorithm and some other fast algorithms. With these primary parameters the feature parameters that are directly related to the gaze direction can be deduced. Then a NN is constructed to indicate the gaze direction after trained by the feature parameters. We have used this method to classify intentional hand gestures in a human-machine interaction system based on gesture recognition. The experimental results show that the proposed method is simple and convenient and can work effectively under changing light conditions.

Eye muscles in humans are arranged such that, by appropriate activation, they allow for eye rotations with three degrees of freedom. Yet it has been known for more than a century that during fixation, while the head is stationary, the eyes do only utilize the horizontal and vertical degrees of rotational freedom while the torsional position of the line of sight is kept constant, i.e., during fixation, the eye is restricted to a two-dimensional (2-D) subspace of the three-dimensional (3-D) space of all possible orientations. This has been first described qualitatively by Donders (1847) who stated that the amount of torsion is fixed for all eye positions, independent of from where the eye has reached a particular position. The geometric consequence of this statement is that all eye positions lie in a 2-D surface. By observing the systematic tilt of afterimages in different gaze directions, Helmholtz was able to determine which 2-D subspace the eye is restricted to. He found, according to what Listing suggested, that the eye positions are not only confined to a surface but to a plane called Listing’s plane. This result, cited as Listing’s law (LL) by Helmholtz (1863), is most simply described if eye positions are expressed in terms of the axes of their rotational displacements from a particular eye position known as primary position and represented by angular position vectors. Then LL states that the eye assumes only those positions that can be reached from primary position by a single rotation about an axis in Listing’s plane, which lies orthogonal to the gaze direction in primary position.

With the development of digital television (DTV) and flat panel display (FPD) technologies, stereoscopic display technology is becoming a new hot spot. Under the stereoscopic display state, the effects of three-dimensional display are mostly concerned about and thus appropriate evaluation criteria and evaluating methods play a very crucial role for the developing of stereoscopic display technology. In this paper, based on full analysis of the related evaluation methods at home and abroad, the effects evaluation of three-dimensional display were focused with parallax perception and parallax assessment and necessary discussions of the research prospects were carried out.

In recent years, eye tracking systems have greatly improved, beginning to play an important role in the assistive technology field. Eye tracking relates to the capability of some devices to detect and measure eye movements, with the aim to precisely identify the user's gaze direction on a screen. The acquired data can then be exploited to provide commands to the computer. In this paper we present WeyeB, a browsing system which allows the two basic Web surfing operations, namely page scrolling and link selection, to be easily performed without using the hands.

Selection of Optimal Frequency Bands of the Electroencephalogram Signal in Eye-brain-computer Interface

Abstrak --- Hijab is a head covering for Muslim women. Hijab can be developed as an application that is implemented based on android. Applications hijab are scattered on android, but the application hijab which exist at present more an assortment of hijab models only. It is considered less supporting the needs of women who hijab. Because the woman was kept at this time included more selective in choosing the model that modern hijab, but in accordance with the Islamic Shari'a. Of these problems led to the idea to create applications based on android hijab, in which modern hijab model provides the appropriate guidance of Islam and to provide information based on the shape of the face veil user at the first capture the face. The methodology used in the making of this application is a method Prototype. The programming language is JAVA (Eclipse). While the method for classification process that distinguishes types of faces in this study using two methods Canny operator and Template Matching Correlation. On the Application hijab, Input as the image of the user's face to be conducted face detection process and display the results of a user's face detection process. Then display the corresponding information hijab Islamic guidance is also based on the shape of the face of the user face detection process. Face shapes used are rounded, long, oval and square with the characteristic that distinguishes every face shape as a reference. While the basics of hadith and verses in the Qur'an make reference to the appropriate information hjab Islamic guidance. With the Android-Based Application hijab is expected of the veiled women to know and implement the hijab correctly. Keywords --- Hijab, Java (Eclipse), Canny operator, Template Matching Correlation.