In recent decades, we have witnessed the evolution of biometric technology from the first pioneering works in face and voice recognition to the current state of development wherein a wide spectrum of highly accurate systems may be found, ranging from largely deployed modalities, such as fingerprint, face, or iris, to more marginal ones, such as signature or hand. This path of technological evolution has naturally led to a critical issue that has only started to be addressed recently: the resistance of this rapidly emerging technology to external attacks and, in particular, to spoofing. Spoofing, referred to by the term presentation attack in current standards, is a purely biometric vulnerability that is not shared with other IT security solutions. It refers to the ability to fool a biometric system into recognizing an illegitimate user as a genuine one by means of presenting a synthetic forged version of the original biometric trait to the sensor. The entire biometric community, including researchers, developers, standardizing bodies, and vendors, has thrown itself into the challenging task of proposing and developing efficient protection methods against this threat. The goal of this paper is to provide a comprehensive overview on the work that has been carried out over the last decade in the emerging field of antispoofing, with special attention to the mature and largely deployed face modality. The work covers theories, methodologies, state-of-the-art techniques, and evaluation databases and also aims at providing an outlook into the future of this very active field of research.

Biometric Antispoofing Methods: A Survey in Face Recognition

Various psychophysical methods have been used to study human haptic perception, although the selection of a particular method is often based on convention, rather than an analysis of which technique is optimal for the question being addressed. In this review, classical psychophysical techniques used to measure sensory thresholds are described as well as more modern methods such as adaptive procedures and those associated with signal detection theory. Details are provided as to how these techniques should be implemented to measure absolute and difference thresholds and factors that influence subjects' responses are noted. In addition to the methods used to measure sensory thresholds, the techniques available for measuring the perception of suprathreshold stimuli are presented. These scaling methods are reviewed in the context of the various stimulus and response biases that influence how subjects respond to stimuli. The importance of understanding the factors that influence perceptual processing is highlighted throughout the review with reference to experimental studies of haptic perception.

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Application of Psychophysical Techniques to Haptic Research

Breath-based human–machine interaction system using triboelectric nanogenerator

Compared to other biometrics, gait is difficult to conceal and has the advantage of being unobtrusive. Inertial sensors, such as accelerometers and gyroscopes, are often used to capture gait dynamics. These inertial sensors are commonly integrated into smartphones and are widely used by the average person, which makes gait data convenient and inexpensive to collect. In this paper, we study gait recognition using smartphones in the wild. In contrast to traditional methods, which often require a person to walk along a specified road and/or at a normal walking speed, the proposed method collects inertial gait data under unconstrained conditions without knowing when, where, and how the user walks. To obtain good person identification and authentication performance, deep-learning techniques are presented to learn and model the gait biometrics based on walking data. Specifically, a hybrid deep neural network is proposed for robust gait feature representation, where features in the space and time domains are successively abstracted by a convolutional neural network and a recurrent neural network. In the experiments, two datasets collected by smartphones for a total of 118 subjects are used for evaluations. The experiments show that the proposed method achieves higher than 93.5% and 93.7% accuracies in person identification and authentication, respectively.

Deep Learning-Based Gait Recognition Using Smartphones in the Wild

This paper surveys the research literature on robust tactile and haptic illusions. The illusions are organized into two categories. The first category relates to objects and their properties, and is further differentiated in terms of haptic processing of material versus geometric object properties. The second category relates to haptic space, and is further differentiated in terms of the observer's own body versus external space. The illusions are initially described and where possible addressed in terms of their functional properties and/or underlying neural processes. The significance of these illusions for the design of tactile and haptic displays is also discussed. We conclude by briefly considering a number of important general themes that have emerged in the materials surveyed.

Tactile and Haptic Illusions

The present study examined our ability to identify the location of a single vibration delivered to the dorsal and/or volar side of the forearm near the wrist. Three participants took part in three absolute identification experiments. In Exps. I and II, a 3-by-3 tactor array was placed on the dorsal and volar side of the wrist, respectively. In Exp. III, two 3-by-3 tactor arrays were placed on both sides of the wrist. Prior to each experiment, the intensities of the tactors were adjusted to be equally loud. Each participant completed a total of 405, 405 and 810 trials for Exps. I, II and III, respectively. The results indicate that on average, only 2 tactor locations can be correctly identified on either the dorsal or the volar side of the wrist, and 4 locations on both sides. The implications of our results for the design of mobile devices are discussed.

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Tactor Localization at the Wrist

As Face Recognition(FR) technology becomes more mature and commercially available in the market, many different anti-spoofing techniques have been recently developed to enhance the security, reliability, and effectiveness of FR systems. As a part of anti-spoofing techniques, face liveness detection plays an important role to make FR systems be more secured from various attacks. In this paper, we propose a novel method for face liveness detection by using focus, which is one of camera functions. In order to identify fake faces (e.g. 2D pictures), our approach utilizes the variation of pixel values by focusing between two images sequentially taken in different focuses. The experimental result shows that our focus-based approach is a new method that can significantly increase the level of difficulty of spoof attacks, which is a way to improve the security of FR systems. The performance is evaluated and the proposed method achieves 100% fake detection in a given DoF(Depth of Field).

Face liveness detection using variable focusing

The detectability and discriminability of virtual haptic gratings were analyzed in the frequency domain. Detection (Exp. 1) and discrimination (Exp. 2) thresholds for virtual haptic gratings were estimated using a force-feedback device that simulated sinusoidal and square-wave gratings with spatial periods from 0.2 to 38.4 mm. The detection threshold results indicated that for spatial periods up to 6.4 mm (i.e., spatial frequencies >0.156 cycle/mm), the detectability of square-wave gratings could be predicted quantitatively from the detection thresholds of their corresponding fundamental components. The discrimination experiment confirmed that at higher spatial frequencies, the square-wave gratings were initially indistinguishable from the corresponding fundamental components until the third harmonics were detectable. At lower spatial frequencies, the third harmonic components of square-wave gratings had lower detection thresholds than the corresponding fundamental components. Therefore, the square-wave gratings were detectable as soon as the third harmonic components were detectable. Results from a third experiment where gratings consisting of two superimposed sinusoidal components were compared (Exp. 3) showed that people were insensitive to the relative phase between the two components. Our results have important implications for engineering applications, where complex haptic signals are transmitted at high update rates over networks with limited bandwidths.

http://www.semifluid.com/wp-content/uploads/2013/03/Cholewiak-Kim-Tan-Adelstein-2010-A-frequency-domain-analysis-of-haptic-gratings.pdf

A Frequency-Domain Analysis of Haptic Gratings

Vision-based hand gesture interactions are natural and intuitive when interacting with computers, since we naturally exploit gestures to communicate with other people. However, it is agreed that users suffer from discomfort and fatigue when using gesture-controlled interfaces, due to the lack of physical feedback. To solve the problem, we propose a novel complete solution of a hand gesture control system employing immersive tactile feedback to the user's hand. For this goal, we first developed a fast and accurate hand-tracking algorithm with a Kinect sensor using the proposed MLBP (modified local binary pattern) that can efficiently analyze 3D shapes in depth images. The superiority of our tracking method was verified in terms of tracking accuracy and speed by comparing with existing methods, Natural Interaction Technology for End-user (NITE), 3D Hand Tracker and CamShift. As the second step, a new tactile feedback technology with a piezoelectric actuator has been developed and integrated into the developed hand tracking algorithm, including the DTW (dynamic time warping) gesture recognition algorithm for a complete solution of an immersive gesture control system. The quantitative and qualitative evaluations of the integrated system were conducted with human subjects, and the results demonstrate that our gesture control with tactile feedback is a promising technology compared to a vision-based gesture control system that has typically no feedback for the user's gesture inputs. Our study provides researchers and designers with informative guidelines to develop more natural gesture control systems or immersive user interfaces with haptic feedback.

Depth Camera-Based 3D Hand Gesture Controls with Immersive Tactile Feedback for Natural Mid-Air Gesture Interactions

In this paper, we propose a new haptic-assisted virtual cane system operated by a simple finger pointing gesture. The system is developed by two stages: development of visual information delivery assistant (VIDA) with a stereo camera and adding a tactile feedback interface with dual actuators for guidance and distance feedbacks. In the first stage, user's pointing finger is automatically detected using color and disparity data from stereo images and then a 3D pointing direction of the finger is estimated with its geometric and textural features. Finally, any object within the estimated pointing trajectory in 3D space is detected and the distance is then estimated in real time. For the second stage, identifiable tactile signals are designed through a series of identification experiments, and an identifiable tactile feedback interface is developed and integrated into the VIDA system. Our approach differs in that navigation guidance is provided by a simple finger pointing gesture and tactile distance feedbacks are perfectly identifiable to the blind.

Kwangtaek Kim

Papers

Tactor Localization at the Wrist

Face liveness detection using variable focusing

A Frequency-Domain Analysis of Haptic Gratings

Depth Camera-Based 3D Hand Gesture Controls with Immersive Tactile Feedback for Natural Mid-Air Gesture Interactions

Stereo camera based virtual cane system with identifiable distance tactile feedback for the blind.