Interaction With Tilting Gestures In Ubiquitous Environments

In this paper, we introduce a tilting interface that controls direction based applications in ubiquitous environments. A tilt interface is useful for situations that require remote and quick interactions or that are executed in public spaces. We explored the proposed tilting interface with different application types and classified the tilting interaction techniques. Augmenting objects with sensors can potentially address the problem of the lack of intuitive and natural input devices in ubiquitous environments. We have conducted an experiment to test the usability of the proposed tilting interface to compare it with conventional input devices and hand gestures. The experiment results showed greater improvement of the tilt gestures in comparison with hand gestures in terms of speed, accuracy, and user satisfaction.Comment: 13 pages, 10 figure

Gesture recognition using mobile phone's inertial sensors

The availability of inertial sensors embedded in mobile devices has enabled a new type of interaction based on the movements or “gestures” made by the users when holding the device. In this paper we propose a gesture recognition system for mobile devices based on accelerometer and gyroscope measurements. The system is capable of recognizing a set of predefined gestures in a user-independent way, without the need of a training phase. Furthermore, it was designed to be executed in real-time in resource-constrained devices, and therefore has a low computational complexity. The performance of the system is evaluated offline using a dataset of gestures, and also online, through some user tests with the system running in a smart phone

Authentication in mobile devices through hand gesture recognition

This article proposes an innovative biometric technique based on the idea of authenticating a person on a mobile device by gesture recognition. To accomplish this aim, a user is prompted to be recognized by a gesture he/she performs moving his/her hand while holding a mobile device with an accelerometer embedded. As users are not able to repeat a gesture exactly in the air, an algorithm based on sequence alignment is developed to correct slight differences between repetitions of the same gesture. The robustness of this biometric technique has been studied within 2 different tests analyzing a database of 100 users with real falsifications. Equal Error Rates of 2.01 and 4.82% have been obtained in a zero-effort and an active impostor attack, respectively. A permanence evaluation is also presented from the analysis of the repetition of the gestures of 25 users in 10 sessions over a month. Furthermore, two different gesture databases have been developed: one made up of 100 genuine identifying 3-D hand gestures and 3 impostors trying to falsify each of them and another with 25 volunteers repeating their identifying 3- D hand gesture in 10 sessions over a month. These databases are the most extensive in published studies, to the best of our knowledge

Analysis of pattern recognition techniques for in-air signature biometrics

As a result of advances in mobile technology, new services which benefit from the ubiquity of these devices are appearing. Some of these services require the identification of the subject since they may access private user information. In this paper, we propose to identify each user by drawing his/her handwritten signature in the air (in-airsignature). In order to assess the feasibility of an in-airsignature as a biometric feature, we have analysed the performance of several well-known patternrecognitiontechniques—Hidden Markov Models, Bayes classifiers and dynamic time warping—to cope with this problem. Each technique has been tested in the identification of the signatures of 96 individuals. Furthermore, the robustness of each method against spoofing attacks has also been analysed using six impostors who attempted to emulate every signature. The best results in both experiments have been reached by using a technique based on dynamic time warping which carries out the recognition by calculating distances to an average template extracted from several training instances. Finally, a permanence analysis has been carried out in order to assess the stability of in-airsignature over time

Design of a 3D mouse using accelerometers

In later years, the number of devices equipped with accelerometers has highly increased, due to their employment in mobile devices for screen orientation and in games for gesture recognition. This thesis debates their advantages and limitations for the creation of a three-dimensional mouse prototype, using a game controller equipped with these sensors. After describing their functioning and highlighting which kind of applications they already support, the work focuses on the design and the implementation of a library for managing a three-dimensional pointer abstraction. In order to address the position drift problem, due to the fact that an accelerometer cannot distinguish between the gravity and input acceleration, two motion-tracking algorithms are proposed: the first one is based only on a three-axial accelerometer and is able to recognize either linear motion on three axes or rotation about two axes. The second one, combining the input of an accelerometer and a gyroscope, can recognize linear motion and rotation on three axes at the same time. The abstraction is tested in a three dimensional environment where the user can move and rotate the pointer, register and analyse movement data. In conclusion are discussed the possible application of the results in windows systems and for future works

Exploring Gesture Recognition in the Virtual Reality Space

This thesis presents two novel modifications to a gesture recognition systemfor virtual reality devices and applications. In doing this it evaluates usersmovements in VR when presented with gestures and uses this information todevelop a continuous tracking system that can detect the start and end of gestures.It also expands on previous work with gestures in games with an implementationof an adaptive database system that has been seen to improve accuracy rates.The database allows users to immediately start using the system with no priortraining and will improve accuracy rates as they spend more time in the game.Furthermore it evaluates both the explicit and continuous recognition systemsthrough user based studies. The results from these studies show promise for theusability of gesture based interaction systems for VR devices in the future. Theyalso provide findings that suggest that for the use case of games continuous systemcould be too cumbersome for users