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Interactive tabletops do not only offer a large surface for collaborative interaction. They also offer quick access to digital tools directly at the table - where a large number of everyday activities take place. Tabletops with an embedded display are generally less flexible and more fragile than ordinary massive tabletops. Physical objects on the tabletop occlude the digital content. In contrast, top-down-projected interfaces using an overhead camera-projector system allow for augmenting arbitrary tables and the object lying on them. However, detecting pointing input only via a camera image captured from above requires robustly recognizing whether a finger or pen touches the tabletop or whether it hovers slightly above it. In this paper, we present a solution for reliably tracking a pen on arbitrary tabletop surfaces. The pen emits infrared light via a tip made of optical fiber. A camera captures position and shape of the light point on the surface. Our open-source tracking algorithm combines heuristics and a machine learning model to distinguish between drawing and hovering. A pilot study with 7 participants shows that that this system can be reliably used for drawing and writing on tabletops. However, occlusion by users’ hands can deteriorate tracking of the pen.

Design using computers is a multidimensional subject. It covers topics from computer graphics and digital imaging to the creation of architectural, mechanical, electrical, industrial and topographical designs and maps. In addition, design using computers includes informatics knowledge regarding the operation and specifications of the peripheral devices of the PC for the input of images or designs, and the peripheral devices used for their performance outside the computer. It also includes knowledge of the operation of the computer and its peripherals in relation to color management and performance. This book attempts to cover at a satisfactory level all the above objects, specializing more, however, in design with CAD software and in particular in AutoDESK AutoCAD, giving the student, researcher and anyone else interested in knowledge and education the possibility to have a complete picture of the subject of Computer Design. In the last two chapters, the book focuses on practical topics around Computer Design to understand the theoretical chapters 1 to 8, focusing on design topics related to the science of Agronomist and Surveyor Engineering by providing material from the laboratory exercises done in the context of the "Design using computers" course at the Department of Rural and Surveying Engineering of the Aristotle University of Thessaloniki and the presentation of topographical design methodologies using AutoCAD software., H σχεδίαση με ηλεκτρονικού υπολογιστές είναι ένα πολυδιάστατο αντικείμενο. Περιλαμβάνει θέματα από τα γραφικά του ΗΥ και την ψηφιακή εικόνα, μέχρι τη δημιουργία αρχιτεκτονικών, μηχανολογικών, ηλεκτρολογικών, βιομηχανικών και τοπογραφικών σχεδίων και χαρτών. Επιπρόσθετα η σχεδίαση με υπολογιστή εμπεριέχει γνώσεις πληροφορικής που αφορούν τη λειτουργία και τις προδιαγραφές των περιφερειακών συσκευών του ΗΥ για την είσοδο εικόνων ή σχεδίων αλλά και των περιφερειακών συσκευών που χρησιμοποιούνται για την απόδοσή τους εκτός του υπολογιστή. Περιλαμβάνει επίσης και τη γνώση της λειτουργίας του υπολογιστή και των περιφερειακών συσκευών του σε σχέση με τη διαχείριση και απόδοση των χρωμάτων. Το παρόν σύγγραμμα επιχειρεί να καλύψει σε ένα ικανοποιητικό επίπεδο όλα τα παραπάνω αντικείμενα, εξειδικεύοντας περισσότερο, όμως, στη σχεδίαση με λογισμικά CAD και ειδικότερα στο AutoCAD της εταιρείας AutoDESK, δίνοντας στον μαθητή, φοιτητή, ερευνητή και οποιονδήποτε άλλον ενδιαφερόμενο για γνώση και μόρφωση τη δυνατότητα να έχει μια πλήρη εικόνα του αντικειμένου της Σχεδίασης με ΗΥ. Στα δύο τελευταία κεφάλαια, το σύγγραμμα επικεντρώνεται σε πρακτικά θέματα γύρω από τη Σχεδίαση με υπολογιστή για την κατανόηση των θεωρητικών κεφαλαίων 1 έως 8, εστιάζοντας σε θέματα σχεδίασης που αφορούν την επιστήμη του Αγρονόμου και Τοπογράφου Μηχανικού με την παροχή υλικού από τις εργαστηριακές ασκήσεις που γίνονται στα πλαίσια του μαθήματος «Σχεδίαση με ΗΥ» στο Τμήμα Αγρονόμων και Τοπογράφων Μηχανικών του Αριστοτελείου Πανεπιστημίου Θεσσαλονίκης και την παρουσίαση μεθοδολογιών σχεδίασης τοπογραφικών σχεδίων με χρήση του λογισμικού AutoCAD.

People with physical disabilities in their upper extremities face serious issues in using classical input devices due to lacking movement possibilities and precision. This article suggests an alternative input concept and presents corresponding input devices. The proposed interface combines an inertial measurement unit and force sensing resistors, which can replace mouse and keyboard. Head motions are mapped to mouse pointer positions, while mouse button actions are triggered by contracting mastication muscles. The contact pressures of each fingertip are acquired to replace the conventional keyboard. To allow for complex text entry, the sensory concept is complemented by an ambiguous keyboard layout with ten keys. The related word prediction function provides disambiguation at word level. Haptic feedback is provided to users corresponding to their virtual keystrokes for enhanced closed-loop interactions. This alternative input system enables text input as well as the emulation of a two-button mouse.

International audience; The control of an avatar’s facial expressions in virtual reality is mainly based on the automated recognition and transposition of the user’s facial expressions. These isomorphic techniques are limited to what users can convey with their own face and have recognition issues. To overcome these limitations, non-isomorphic techniques rely on interaction techniques using input devices to control the avatar’s facial expressions. Such techniques need to be designed to quickly and easily select and control an expression, and not disrupt a main task such as talking. We present the design of a set of new non- isomorphic interaction techniques for controlling an avatar facial expression in VR using a standard VR controller. These techniques have been evaluated through two controlled experiments to help designing an interaction technique combining the strengths of each approach. This technique was evaluated in a final ecological study showing it can be used in contexts such as social applications.

Virtual Reality (VR) has made its way into everyday life. While VR delivers an ever-increasing level of immersion, controls and their haptics are still limited. Current VR headsets come with dedicated controllers that are used to control every virtual interface element. However, the controller input mostly differs from the virtual interface. This reduces immersion. To provide a more realistic input, we present Flyables, a toolkit that provides matching haptics for virtual user interface elements using quadcopters. We took five common virtual UI elements and built their physical counterparts. We attached them to quadcopters to deliver on-demand haptic feedback. In a user study, we compared Flyables to controller-based VR input. While controllers still outperform Flyables in terms of precision and task completion time, we found that Flyables present a more natural and playful way to interact with VR environments. Based on the results from the study, we outline research challenges that could improve interaction with Flyables in the future.

Portable assistive technology systems are developed to enhance the capability of persons with disabilities. One of the most important senses for humans is vision. Vision is the most important sense which helps us in understanding the perception of the surrounding environment. Visually impaired persons face a lot of difficulty in understanding the perception around them, particularly in outdoor environment where objects are continuously changing and moving from one place to another. Object detection solutions would greatly assist visually impaired persons in avoiding from the barriers which they face in their daily routine life. The aim of the object detection system is to provide a simple, user-friendly, handy, economical and efficient solution for the visually impaired persons. Motive of this system is to develop a solution that detects the objects present using camera, as the input device in real time and communicate the same to the user using smartphone through headphones. The system would be using an audio device such as speakers or headphones in providing the information about objects to assist the visually impaired persons. The proposed system helps in identifying and avoiding the objects both in outdoor and indoor environments that affect day to day life activities and occupational performance of the visually impaired persons. The information about the objects in surrounding environment would be very much helpful to the visually impaired persons in their daily life.

We present a method to track a smartphone in VR using a fiducial marker displayed on the screen. Using WebRTC transmission protocol, we capture smartphone touchscreen input and the screen contents, copying them to a virtual representation in VR. We present two Fitts’ law experiments assessing the performance of selecting targets displayed on the virtual smartphone screen using this method. The first compares direct vs. indirect input (i.e., virtual smartphone co-located with the physical smartphone, or not), and reveals there is no difference in performance due to input indirection. The second experiment assesses the influence of input scaling, i.e., decoupling the virtual cursor from the actual finger position on the smartphone screen so as to provide a larger virtual tactile surface. Results indicate a small effect for extreme scale factors. We discuss implications for the use of smartphones as input devices in VR.

To reduce frustration while performing no-risk tasks (e.g. in training and games) for BCI users, we propose increasing their perceived level of control through fabricated input - system-generated positive task outcomes. Two surrogate BCI studies injected fabricated input creating additional positive task outcomes to a 50\% baseline. Users' perceived control increased significantly compared to the 50\% baseline. In turn, frustration levels decreased. Fabricated input worked equally well in a game story context that provided an emotional stake in the protagonist's success and a simpler task lacking such incentives. People’s number of input attempts determined perceived control more than our controlled ratios of positive to negative task outcomes. Delays between users’ input attempts and subsequent fabricated inputs further moderated their perceived control.

In this paper, we present a method to integrate sensing capabilities into 3D printable metamaterial structures comprised of cells, which enables the creation of monolithic input devices for HCI. We accomplish this by converting select opposing cell walls within the metamaterial device into electrodes, thereby creating capacitive sensors. When a user interacts with the object and applies a force, the distance and overlapping area between opposing cell walls change, resulting in a measurable capacitance variation. To help designers create interactive metamaterial devices, we contribute a design and fabrication pipeline based on multi-material 3D printing. Our 3D editor automatically places conductive cells in locations that are most affected by deformation during interaction and thus are most suitable as sensors. On export, our editor creates two files, one for conductive and one for non-conductive cell walls, which designers can fabricate on a multi-material 3D printer. Our applications show that designers can create metamaterial devices that sense various interactions, including sensing acceleration, binary state, shear, and magnitude and direction of applied force.

With the portable and affordable gaze input devices being marketed for end users, gaze-based interactions were getting increasingly popular. Unfortunately, the understanding about the dominant task of gaze input, i.e. eye pointing task, was still not sufficient although a performance model had been specifically proposed in previous study because of that 1) the original model was based on a specific circular target condition, without the ability to predict the performance of acquiring conventional rectangular targets and that 2) there was a lack of explanation from the perspective of the anatomical structure of the eyes. In this paper, we proposed a 2D extension to take account of more general target conditions. Carrying out two experiments, we evaluated the effectiveness of the new model and furthermore we found that the index of difficulty that we redefined for 2D eye pointing (IDeye) was able to properly reflect the asymmetrical impacts of target width and height, and consequently the IDeye model could more accurately and properly predict the performance when acquiring 2D targets than Fitts’ law, no matter what kind of saccades or eye orientations (i.e. saccadic eye movement directions) was employed to acquire the desired targets. According to the results, we provided more useful implications and recommendations for gaze-based applications.

This paper presents, the enhancement of Electronic Voting Machine (EVM) performance using fingerprint and face recognition. In democratic countries, the EVM plays a vital role in the election process. Even though it has more benefits; still the malpractices are continued due to manual verification of electoral documents for all elections in democratic countries. In this proposed method EVM with biometric fingerprint and face recognition devices are used to overcome this problem. To conquer the issues existing in the election process for voter identification the biometric fingerprint and web cameras are introduced in the EVMs. The people at the polling booth need to put the finger in the fingerprint equipment and face to be captured by the web camera provided to recognize them. The controller fetches the data from the input devices and compares it with the database to enable the polling device to cast their votes. In practice, due to some technical issue either in the input devices or from the voter side the election process will be continued by document verification. In the polling booths, the presiding officers are having the right to enable the polling device by pressing the enable button after document verification. The performance of the proposed method was validated with EVM successfully.

HDL (Hardware Description Languages) is really important tool for all digital designers. After they have learned about Verilog or VHDL (the abbreviation for Very High Speed Integrated Circuit Hardware Description Language) System, digital designers will be capable to detail digital systems much quicker than if they would have to create all entire schematics. The HDLs are used for simulation and synthesis. It is very important to involve students passionate about digital design to use such modern languages because they can use them successfully in their future career. This paper aims to present an HDL-based test stand that can be implemented using a Nexys2 circuit board which is a complete, ready-to-use circuit development platform based on a Xilinx Spartan 3E FPGA (Field Programmable Gate Array). The Nexys2 board incorporates several input devices, output devices, and data ports, allowing various designs to be implemented with no need for any other components. Basically, the test stand will offer the possibility to choose the number of inputs (three or four) and to establish six basic functions that can be selected for verification, the result being displayed using the BCD (Binary Coded Decimal) display system integrated in the board. The inputs will be represented by the set of push buttons available on the board.

Nowadays, there is a huge inclination of youngsters and adults towards video games and of course in our childhood everyone might definitely have experienced it. However, we are controlling the game using typical input devices such as mouse, keyboard, joystick, etc but how about, if we control the game using our hand gestures ? These days we have lots of game controllers that are surpassing the gaming experience however they are quite expensive too. Through this project we have designed our own game controlling glove using Arduino. In addition we have also developed a car game using UNITY 3D. The areas of IOT and hand gesture recognition will be explored by this project.

Gesture air-writing is an advanced nontouching interaction method that replaces traditional typewriter keyboards, touch screens and other input devices. Due to its low power consumption, noncontact detection and independence from light conditions, millimeter wave radar has become a valuable gesture air-writing solution. In this paper, we proposed a prototype of a gesture air-writing tracking system that is based on the 24-GHz frequency-modulated continuous-wave (FMCW) radar system-on-chip (SoC). The transmitted chirp signal of this radar chip covers up to a 4-GHz bandwidth, which provides sufficient range resolution to track hand gestures. With the development of single input, multiple output (SIMO) antennas, the air-writing symbols can be reconstructed in an observation plane. A system design and signal processing algorithm for gesture air-writing applications is proposed for the prototype system in this paper. To test the performance of the proposed method, experiments with cases of five simple gestures, air-writing numbers and letter tracking are carried out. The experimental results verify the efficiency and accuracy of the proposed method.

The voice-based technology is a promising alternative input modality to the conventional computer input devices, such as keyboards and mice. For mobility-impaired people who cannot use the traditional computer input devices, a voice-based interactive solution is highly desirable. Although some grid-based cursor control systems that use speech recognition show potentials, they come with limitations in processing time and difficulties in real-time applications. Since they are not natural enough to use, it is very slow to drill down the grid, and the point cursor selection range is prone to errors, and people need a more efficient and natural choice. To address these limitations, this paper proposes two novel speech-based target selection techniques: grid-based region selection (hereinafter referred to as “Region Selection”) and grid-based target search (hereinafter referred to as “Target Search”). Region Selection allows users to select targets directly using the selected area. Target Search permits users to move the cursor to a target in a specified direction. Experiments are designed and conducted to analyze the impacts of target size and target density on performance and processing time. The experimental results and comparison study with traditional solution show that both Region Selection and Target Search improve the participants' accuracy of target selection and reduce the processing time, especially for small targets.

The myoelectric interfaces are being used in rehabilitation technology, assistance and as an input device. This review focuses on an insightful analysis of the data acquisition system of EMG signals from these interfaces. According to applications reported in research articles of the last five years, the properties of the sensors, the number of channels, the pre-processing of the EMG signal, as well as the software and hardware used were identified. This analysis was performed for the following applications: monitoring of muscular activation for rehabilitation, muscle activation plans, and identification of possible pathologies, exoskeletons, electric of wheelchairs, prosthetics control, myoelectric bracelets, handwriting recognition and silent speech recognition. The results presented in this review become a guide of recommendations for the myoelectric signal processing according to the application of the interface. The main developments, degrees of research and open challenges are also presented in this direction.

In this article, a pen-type device that enables three-dimensional (3D) human-computer interaction is presented. This device is based on a high-precision 3D ultrasonic (US) positioning method, which can achieve millimeter-level accurate 3D positioning and six degrees of freedom (6DoF) within a working range of 4 m × 1.5 m × 1.5 m. The 3D positioning of the electronic pen is realized by a highprecision time-of-flight (TOF) detection method based on dynamic thresholding and zero-crossing detection as well as a multigroup positioning coordinate averaging method. During the 3D positioning process, correlation filtering is adopted to process the received US signals and suppress any interference signals below 20 kHz and above 60 kHz. The positioning method can achieve a high positioning accuracy without any complex calculations. The attitude of the electronic pen is measured using an inertial measurement units (IMUs). To demonstrate the positioning accuracy of the proposed device, a total of 108 test positions are uniformly set in the workspace, and static and dynamic positioning accuracy experiments are carried out at all test positions. The experimental results show static and dynamic positioning errors of less than 0.35 mm and less than 1.0 mm, respectively, which indicate a high positioning accuracy. The proposed device can provide 6DoF and enable writing in 3D. Therefore, the device can meet the common requirements of a 3D human-computer interaction interface.

Challenge-response (CR) is an effective way to authenticate users even if the communication channel is insecure. Traditionally CR authentication relies on one-way hashes and shared secrets to verify the identities of users. Such a method cannot cope with an insider attack, where a user can obtained the secret (i.e., the response) from a legitimate user. To cope with it, we design a biometric-based CR authentication scheme (hereafter MoCRA ), which is derived from the motions as a user operates emerging depth-sensor- based input devices, such as a Leap Motion controller. We envision that to authenticate a user, MoCRA randomly chooses a string (e.g., a few words), and the user has to write the string in the air. Using Leap Motion, MoCRA captures the user's writing movements and then extracts his / her handwriting style. After verifying that what the user writes matches what is asked for, MoCRA leverages a Support Vecter Machine (SVM) with co-occurrence matrices to model the handwriting styles and can reliably authenticate users, even if what they write is completely different every time. Evaluated on data from 24 subjects over 7 months, MoCRA managed to verify a user with an average of $1.18\%$ 1 . 18 % (Equal Error Rate) EER and to reject impostors with $2.45\%$ 2 . 45 % EER.

The demand for wearable technology devices has changed in recent years, due to the fact that wearable devices (WDs) make our lives easier and more comfortable than ever before. WDs are often seen as an extension to mobile devices such as smartphones even thought the size, shape and physical specifications, i.e., the form factors are completely different. The core features of WDs are always accessible and available to users while sole input devices, e.g. keyboard does not exist. In this case, the traditional authentication methods in which users type in passwords on the system can not apply to authenticate WDs. Therefore, this paper introduces an Authentication Framework for Wearable Devices (AFWD) that basically includes an authentication model designed for WDs, capable of creating reliable and secure authentication techniques. Subjective and objective assessment of the AFWD showed that it provides usability, deployability, and security and that people are willing to use it if available. Such a framework is crucial for Intelligent Transportation Systems (ITS) as it provides reliability and trustworthiness of the data transmitted via WDs.

Among many of the fastest growing research fields, sign language recognition is one of the top. Deaf and dumb community uses sign language to express their ideas or views. Sign Language is a methodical coded language where meanings are assigned to every gestures. Many techniques have been developed with the advancement of science and technology to minimize the problem for speech and hearing disabled. The mode of such communication is part of human computer interaction. Hand gesture plays an important role here. The interaction with computer through gesture removes the use of conventional input devices like mouse and keyboards. To create a strong interface between user and computer, recognition of gesture is important. In this paper, a hand gesture recognition method based on multiscale density features is proposed. Depth images of numerals of American Sign Language are considered in this work and recognition rate of 98.20% is obtained, which is comparable with related state-of-the art methods.

In this paper, a solution is presented to support both existing and future movement rehabilitation applications. The presented method combines the advantages of human-computer interaction-based movement therapy, with the cognitive property of intelligent decision-making systems. With this solution, therapy could be fully adapted to the needs of the patients and conditions while maintaining a sense of success in them, thereby motivating them. In our modern digital age, the development of HCI interfaces walks together with the growth of users’ needs. The available technologies have limitations, which can reduce the effectiveness of modern input devices, such as the Kinect sensor or any other similar sensors. In this article, multiple newly developed and modified methods are introduced with the aim to overcome these limitations. These methods can fully adapt the movement pattern recognition to the users' skills. The main goals are to apply this method in movement rehabilitation, where the supervisor, a therapist can personalize the rehabilitation exercises due to the Distance Vector-based Gesture Recognition (DVGR), Reference Distance-based Synchronous/Asynchronous Movement Recognition (RDSMR/RDAMR) and the Real-Time Adaptive Movement Pattern Classification (RAMPC) methods.

Las interfaces de entrada para juegos (Gamepad) proporcionan distintas perspectivas en cuanto a jugabilidad, siendo un componente fundamental para mejorar el rendimiento y los resultados durante la interacción con el entorno virtual. El propósito de este estudio cualitativo, es identificar el comportamiento de los atributos que caracterizan la jugabilidad en diferentes interfaces de entrada sobre un simulador para entrenamiento de cirugía laparoscópica, asistida por robot PA-10. Para ello se tuvo en cuenta algunos atributos de jugabilidad como: eficiencia, efectividad, juego mecánico, inmersión, ergonomía, adaptación y satisfacción. Los cuales fueron comparados para mostrar el efecto que se produjo en ellos al interactuar con los dispositivos de entrada y el sistema.

Machine learning is an application of artificial intelligence that focuses on the development of computer algorithms which learn automatically by extracting patterns from the data provided. Machine learning techniques can be efficiently used for a problem with a large number of parameters to be optimized and also where it is infeasible to develop an algorithm of specific instructions for performing the task. Here, we combine the finite element simulations and machine learning techniques for the prediction of mode effective indices, power confinement, and coupling length of different integrated photonics devices. Initially, we prepare a dataset using COMSOL Multiphysics and then this data is used for training while optimizing various parameters of the machine learning model. Waveguide width, height, operating wavelength, and other device dimensions are varied to record different modal solution parameters. A detailed study has been carried out for a slot waveguide structure to evaluate different machine learning model parameters including number of layers, number of nodes, choice of activation functions, and others. After training, this model is used to predict the outputs for new input device specifications. This method predicts the output for different device parameters faster than direct numerical simulation techniques. Absolute percentage error of less than 5% in predicting an output has been obtained for slot, strip, and directional waveguide coupler designs. This study paves the step towards using machine learning based optimization techniques for integrated silicon photonics devices.

Wearable computing platforms, such as smartwatches and head-mounted mixed reality displays, demand new input devices for high-fidelity interaction. We present AuraRing, a wearable magnetic tracking system designed for tracking fine-grained finger movement. The hardware consists of a ring with an embedded electromagnetic transmitter coil and a wristband with multiple sensor coils. By measuring the magnetic fields at different points around the wrist, AuraRing estimates the five degree-of-freedom pose of the ring. We develop two different approaches to pose reconstruction---a first-principles iterative approach and a closed-form neural network approach. Notably, AuraRing requires no runtime supervised training, ensuring user and session independence. AuraRing has a resolution of 0.1 mm and a dynamic accuracy of 4.4 mm, as measured through a user evaluation with optical ground truth. The ring is completely self-contained and consumes just 2.3 mW of power.

This paper presents an RF-based assistive technology for voice impairments (i.e., dysphonia), which occurs in an estimated 1% of the global population. We specifically focus on acquired voice disorders where users continue to be able to make facial and lip gestures associated with speech. Despite the rich literature on assistive technologies in this space, there remains a gap for a solution that neither requires external infrastructure in the environment, battery-powered sensors on skin or body-worn manual input devices. We present RFTattoo, which to our knowledge is the first wireless speech recognition system for voice impairments using batteryless and flexible RFID tattoos. We design specialized wafer-thin tattoos attached around the user's face and easily hidden by makeup. We build models that process signal variations from these tattoos to a portable RFID reader to recognize various facial gestures corresponding to distinct classes of sounds. We then develop natural language processing models that infer meaningful words and sentences based on the observed series of gestures. A detailed user study with 10 users reveals 86% accuracy in reconstructing the top-100 words in the English language, even without the users making any sounds.

Voice-over-IP (VoIP) software are among the most widely spread and pervasive software, counting millions of monthly users. However, we argue that people ignore the drawbacks of transmitting information along with their voice, such as keystroke sounds—as such sound can reveal what someone is typing on a keyboard. In this article, we present and assess a new keyboard acoustic eavesdropping attack that involves VoIP, called Skype & Type ( S&T ). Unlike previous attacks, S&T assumes a weak adversary model that is very practical in many real-world settings. Indeed, S&T is very feasible, as it does not require (i) the attacker to be physically close to the victim (either in person or with a recording device) and (ii) precise profiling of the victim’s typing style and keyboard; moreover, it can work with a very small amount of leaked keystrokes. We observe that leakage of keystrokes during a VoIP call is likely, as people often “multi-task” during such calls. As expected, VoIP software acquires and faithfully transmits all sounds, including emanations of pressed keystrokes, which can include passwords and other sensitive information. We show that one very popular VoIP software (Skype) conveys enough audio information to reconstruct the victim’s input—keystrokes typed on the remote keyboard. Our results demonstrate that, given some knowledge on the victim’s typing style and keyboard model, the attacker attains top-5 accuracy of 91.7% in guessing a random key pressed by the victim. This work extends previous results on S&T , demonstrating that our attack is effective with many different recording devices (such as laptop microphones, headset microphones, and smartphones located in proximity of the target keyboard), diverse typing styles and speed, and is particularly threatening when the victim is typing in a known language.

This paper explores the human capacity to use visual feedback to compensate for directional mismatches between input devices and cursor motions in a standardized pointing task. Sixteen participants completed blocks of 64 trials as the directional mismatch between the input device and cursor motion was incremented clockwise by 7.5° over thirteen blocks, from 0° to 90°. At 90°, a vertical motion of the mouse mapped to a cursor motion directly to the right. Participants were robust to these acclimated directional mismatches up to 30°, at which point pointing performance began to decline. The findings have application in understanding the robustness of traditional input methods, as well as in virtual reality where visual feedback mismatches can be used for steering physical motions to make better use of constrained physical space or to reuse tactile stimuli.

A low-cost microprocessor-based system-on-chip is a key building block for the Internet of Things. To perform sensing, computing, and communications, it requires multiple analog, digital, and mixed-signal circuits. Integrating those circuits, however, increases silicon area and cost. It is particularly expensive to add dedicated hardware for low duty-cycled functions such as environment sensing. In this letter, we reduce such overhead and introduce a design approach that can dynamically transform an 8-kB 6T SRAM into a 6-b stochastic ADC having a 300-mVPP input range. Incurring only a 740- $\mu \text{m}^{2}$ (0.93%) area overhead, this approach provides a data-conversion capability at very low cost.

The representation of an object’s outline with polygons or more specific shapes is the first choice for interactive outline acquisition. Usually, an operator has to select appropriate tools to capture an object’s outline according to his or her notion of the shape with its underlying construction principles. We propose a modeless approach guided by geometric reasoning, i.e., the user does not have to select operation modes according to his or her model. To cope with modern input devices such as touch pens, styluses, or fingers, we consider strokes as input in arbitrary order. By approximating theses strokes with straight line segments, we obtain estimated levels of noise accounting for the uncertainty of the acquisition. These straight line segments are the basis for the subsequent hypothesis generation to recognize geometric relations. After identifying sets of consistent and nonredundant constraints, we enforce these constraints in an adjustment process. To demonstrate the usability of the proposed approach, we capture the outlines of buildings and roof areas in true orthophotos of a benchmark data set.

The present study investigated the effects of different joint-based interactive methods and control-display gains on performance and usability for distant pointing by using ISO 9241–9 test procedures. Ten healthy participants performed multi-directional tapping tests with three joint-based interactive methods (wrist-, elbow-, and shoulder-based interactive methods) and three CD gains (0.6, 1.0, and 1.7) by using an air mouse as the input device. The experimental results indicated that the wrist-based interactive method is a better interactive method for tasks where pointing speed is the highest priority and the 1.7 CD gain, which was found to cause significantly higher MT and ER and lower TP and subjective usability rating scores than wrist- and elbow-based pointing, should be avoided in distal pointing tasks. Furthermore, the best suggested CD gains for the wrist-based interactive method are 1.0 and 1.7. The recommended CD gain setting of the elbow-based interactive method is 0.6, and 1.0 CD gain is feasible for the shoulder-based interactive method.

Despite active research in input device development, the visually impaired community still find difficulty in interacting with computers. Braille and other conventional methods have limitations while inputting data to the computer due to their vision loss. Gesture-based interaction can offer them a new vista of computer interaction. However, one needs to consider their performance and preference towards hand gesture. So, a gesture elicitation study is done with 25 visually impaired users. A quantitative rating analysis is performed with them, and an optimal set of gestures is obtained. Further, a dactylology is proposed using which visually impaired users can interact with computers. A recognition module is also presented to recognise the dactylology symbols.

The interaction technology in general is inseparable from the rapid development of Human-Computer Interaction technology or Human and Computer Interaction. Human and computer mouse interactions are called Virtual Mouse. Virtual mouse is designed for users to be able to interact directly with computers without using input devices such as conventional mice but using their hands as driving objects or using other media such as colors. In this research, testing is done on how to track an object that moves in order to do the mouse by using an intermediary in the form of an image processing-based webcam video that is taken in real-time using object tracking in the form of three color variables arranged based on RGB composition using the optical flow method in detecting its movement. Based on research that has been carried out as a whole the color object used as a pointer controller or mouse with the optical flow method can be detected properly in every condition.

Fingertip computing has seen increased interest through miniaturized smart-rings for augmenting digital peripherals. One key advantages of such always-available input devices is the non-necessity to hold a device for interaction, as it remains affixed to a finger for access when needed. Such a wearable device makes it possible to interaction with content even when the hand is encumbered, by grasping or holding objects. Our investigation aims at understanding the properties of this fundamental smart-ring advantage. We designed a smart-ring prototype, ARO (in-Air, on-Ring, on-Object interaction), which facilitates input while grasping objects. To better identify interaction possibilities, we present the results of an elicitation study through which we grouped various forms of micro-gestures possible with ARO while holding objects under different grasp requirements. We then explored the ability for users to perform different navigation tasks (i.e. zooming and panning) using the smart-ring with encumbered hands. In our studies, users were most efficient when using either In-air or On-ring interactions, in comparisons to gestures detected On-object. Furthermore, In-air was the most preferred by our participants. Based on our findings, we conclude with recommendations for the design of future smart-rings and fingertip devices at large, to allow efficient interaction while hands are encumbered.