Jože Guna

An Analysis of the Precision and Reliability of the Leap Motion Sensor and Its Suitability for Static and Dynamic Tracking

We present the results of an evaluation of the performance of the Leap Motion Controller with the aid of a professional, high-precision, fast motion tracking system. A set of static and dynamic measurements was performed with different numbers of tracking objects and configurations. For the static measurements, a plastic arm model simulating a human arm was used. A set of 37 reference locations was selected to cover the controllers sensory space. For the dynamic measurements, a special V-shaped tool, consisting of two tracking objects maintaining a constant distance between them, was created to simulate two human fingers. In the static scenario, the standard deviation was less than 0.5 mm. The linear correlation revealed a significant increase in the standard deviation when moving away from the controller. The results of the dynamic scenario revealed the inconsistent performance of the controller, with a significant drop in accuracy for samples taken more than 250 mm above the controllers surface. The Leap Motion Controller undoubtedly represents a revolutionary input device for gesture-based human-computer interaction; however, due to its rather limited sensory space and inconsistent sampling frequency, in its current configuration it cannot currently be used as a professional tracking system.

Intuitive gesture based user identification system

We present an intuitive and very easy to use implicit gesture based identification system that is especially suited for security-wise non-critical applications, such as the user login in the multimedia services. The term “implicit gesture” in our work refers to a natural physical hand manipulation performed by the user who takes hold of the control device and simply picks it up from its neutral motionless position - a “pick-up” gesture. For reference with other related systems, explicit and well defined personal name identification gestures were used as well. User evaluation study results show that 100% recognition accuracy was achieved when using explicit identification signature gestures and over 91% recognition accuracy was achieved when using the implicit “pick-up” gesture. Performance of the proposed system is comparable to results of other respectable related works when using explicit identification gestures, while also showing that implicit gesture based user identification is possible and viable.

Evaluation of Leap Motion Controller with a High Precision Optical Tracking System

The paper presents an evaluation of the performance of a Leap Motion Controller. A professional optical tracking system was used as a reference system. 37 stationary points were tracked in 3D space in order to evaluate the consistency and accuracy of the Controller’s measurements. The standard deviation of these measurements varied from 8.1 μm to 490 μm, mainly depending on the azimuth and distance from the Controller. In the second part of the experiment, a constant distance was provided between two points, which were then moved and tracked within the entire sensory space. The deviation of the measured distance changed significantly with the height above the Controller. The sampling frequency also proved to be very non-uniform. The Controller represents a revolution in the field of gesture-based human-computer interaction; however, it is currently unsuitable as a replacement for professional motion tracking systems.

MedReminder - an interactive multimedia medical application for the IPTV environment

We present the MedReminder, an interactive multimedia medical application, integrated into an existing IPTV service framework. The MedReminder application is implemented within XBMC multimedia platform and is integrated alongside interactive TV live and on demand multimedia services, providing easy to use and intuitive user experience. It is a client-server based application connecting different target user roles: doctors as medicine prescribers, patients as medicine consumers and patient caregivers. It allows for a centralized collection of medicine related reminder information. Consequently, the system provides user notifications on TV screen and through other communication channels, such as SMS messages, e-mail and telephone calls, which are used in case the consumption of prescribed medicine has not been confirmed. Several use case scenarios are discussed including the possibility of dynamic medicine prescriptions, based on doctors remote readings of patients medical parameters (e.g. blood pressure, body weight, temperature etc.), using the integrated personal health system.

Introduction to the special section on Artificial Intelligence and Computer Vision

The integration of artificial intelligence and computer vision technologies has become a topic of increasing interest for both researchers and developers from academia and industry worldwide. It is foreseeable that artificial intelligence will be the main approach to the next generation computer vision research. The explosion of artificial intelligence algorithms and rapidly growing computational power have significantly expanded the possibility of computer vision. New challenges have also been brought to the vision community. The aim of this special issue is to provide a platform to share up-to-date scientific achievements in this field. From a total of 46 papers submitted to this special section, 10 high-quality articles were selected, resulting in an acceptance rate of 21.7%. Each paper was peer reviewed by three or more experts during the assessment process. The selected articles have exceptional diversity in terms of artificial intelligence and computer vision techniques and applications. They represent the most recent development in both theory and practice. The contributions of these papers are briefly described as follows.

Capturing the mood: Evaluation of the moodstripe and moodgraph interfaces

This study presents an evaluation of two interfaces for gathering user feedback in online surveys. We evaluated the intuitiveness, usability and time complexity of the proposed interfaces in comparison to the more standard approaches. Over 900 users first participated in an online survey exploring the influence of mood on their emotional responses to music and colors. We included several new interfaces in this survey, so after it was completed, users were asked to complete a second survey where they evaluated various aspects of the interfaces. Our analysis shows reduced time complexity and increased intuitiveness of the new interfaces, compared to standard approaches, resulting in lower mental difficulty and frustration of participants.

Users’ viewpoint of usability and user experience testing procedure - gaining methodological insights in a case of an interactive HbbTV application

We present a novel meta-methodological approach for the user experience and usability methodology procedure evaluation, shown in an example of the user experience and usability study of an interactive HbbTV application. The idea behind this research is not only to evaluate and improve the TV-WEB service but also to gain insights how the participants perceived the whole Ux evaluation procedure itself. The research questions focused mainly on the time complexity (temporal demand) and the frustration level of the TV-WEB evaluation procedure. Additionally the appropriateness of the selected content used, interface and interaction design, and the service impressions and satisfaction/payment related questions was sought. A special questionnaire based on the NASA TLX standard test is presented. The concept has been successfully implemented in several live field trials in three countries (BiH, Serbia and Montenegro). In the user experience and usability study of the service itself more than 150 participants were involved, of those 35 took part in the meta-methodology study. The feedback was quantitatively evaluated on a 7-point Likert scale, with “1” indicating the best positive feedback, “4” neutral/undecided feedback and “7” the most negative feedback. The quantitative average summary results obtained in the three evaluation studies were 1.30 for both the BiH and Serbia test study cases and the score of 1.22 for the test study case in Montenegro. These results show that a great majority of the participants found the whole evaluation procedure time-wise and frustration-wise undemanding, with appropriate content, presentation style and overall attitude towards them. By using this approach it was possible to improve the user experience and usability methodology used, producing more reliable results and providing better user experience in the final version of the product as well as providing a pleasant experience during the testing of the product.

Influence of video content type on users’ virtual reality sickness perception and physiological response

Abstract Virtual Reality (VR) sickness (Cybersickness) is an affliction and a challenge, common to users of virtual environments. We therefore asked ourselves this research question: “Can video content type influence users’ VR sickness and physiological response?” We conducted a study with 26 participants, who watched two omnidirectional videos of different content types (neutral and action content) on five distinct video conditions: 2D TV screen, three generations of Oculus Rift VR HMDs (DK1, DK2 and CV1) and on the mobile Samsung GearVR HMD. The Simulator Sickness Questionnaire and the Subjective Units of Distress Scale in combination with the measurement of the physiological parameters (electrodermal activity and skin temperature, respiratory frequency and heart rate) were used to assess the VR sickness effects. The results show that video content type as well as users’ background preferences (preference to adrenaline sports) affected the users’ VR sickness perception. Considering various video conditions, significantly less VR sickness effects were reported with the TV condition than with any VR devices. The results of the subjective questionnaires were correlated with the objective physiological measurements, whereby skin conductance strongly correlated with the VR sickness effects. The effects were also more pronounced in cases of action video content type. Furthermore, we show there is a strong correlation when assessing the VR sickness effects using subjective questionnaire-based methods (the Simulator Sickness Questionnaire and the Subjective Units of Distress Scale) of various complexity, indicating the simple methods (only one question), can effectively be used as well.

Suitability of Inexpensive Eye-Tracking Device for User Experience Evaluations

We present the results of a study evaluating the suitability of an inexpensive eye-tracking device for the enhancement of user experience evaluations. Ensuring a comfortable user experience is an important part of the mobile application design process. Evaluation of user experience is usually done through questionnaires and interviews, but it can be improved using eye tracking sensors for user experience studies. We conducted a user experience study of DriveGreen, a mobile application devoted to ecodriving for a transition to a low-carbon society. We used an inexpensive eye-tracking device in addition to standard User Experience Questionnaire and Single Ease Question questionnaires. The results show that the inexpensive eye-tracking device data correlate with data from User Experience Questionnaire and Single Ease Question questionnaires and interviews with users. We conclude that an enhancement of user experience evaluations with inexpensive eye-tracking device is possible.

Motor Anomaly Detection for Aerial Unmanned Vehicles Using Temperature Sensor

Aerial unmanned vehicle is widely used in many fields, such as weather observation, framing, inspection of infrastructure, monitoring of disaster areas. However, the current aerial unmanned vehicle is difficult to avoid falling in the case of failure. The purpose of this article is to develop an anomaly detection system, which prevents the motor from being used under abnormal temperature conditions, so as to prevent safety flight of the aerial unmanned vehicle. In the anomaly detection system, temperature information of the motor is obtained by DS18B20 sensors. Then, the reinforcement learning, a type of machine learning, is used to determine the temperature is abnormal or not by Raspberrypi processing unit. We also build an user interface to open the screen of Raspberrypi on laptop for observation. In the experiments, the effectiveness of the proposed system to stop the operation state of drone when abnormality exceeds the automatically learned motor temperature. The experimental results demonstrate that the proposed system is possibility for unmanned flight safely by controlling drone from information obtained by attaching temperature sensors.