Remote tutoring has gained significant traction due to technological advances, primarily relying on video-conferencing tools. However, these tools are not specifically designed for tutoring. Positive tutoring experiences rely on interaction with and immediate feedback from the tutor. Moreover, traditional methods like writing, reading, and drawing in physical spaces enhance learning outcomes. Integrating these methods with physical materials and digital remote guidance could improve remote learning experiences. A technology that enables this integration is spatial augmented reality (SAR), which utilizes projection to integrate digital content into the physical world. This work introduces a Spatial Augmented Reality (SAR) remote tutoring tool that enables augmented annotations and projected video streams. We conducted a between-subject lab study (N=18) comparing learning experiences in remote tutoring between standard video conferencing tools and the introduced Spatial Augmented Reality (SAR) tool. Qualitative analysis revealed the Spatial Augmented Reality (SAR) system's benefits over video conferencing, specifically immediate feedback, in-situ annotations, improved interactivity, and enhanced social presence.

Scanning everyday objects with depth sensors is the state-of-the-art approach to generating point clouds for realistic 3D representations. However, the resulting point cloud data suffers from outliers and contains irrelevant data from neighboring objects. To obtain only the desired 3D representation, additional manual segmentation steps are required. In this paper, we compare three different technology classes as independent variables (desktop vs. tablet vs. virtual reality) in a within-subject user study (N = 18) to understand their effectiveness and efficiency for such segmentation tasks. We found that desktop and tablet still outperform virtual reality regarding task completion times, while we could not find a significant difference between them in the effectiveness of the segmentation. In the post hoc interviews, participants preferred the desktop due to its familiarity and temporal efficiency and virtual reality due to its given three-dimensional representation.

Cross-reality systems empower users to transition along the reality-virtuality continuum or collaborate with others experiencing different manifestations of it. However, prototyping these systems is challenging, as it requires sophisticated technical skills, time, and often expensive hardware. We present VRception, a concept and toolkit for quick and easy prototyping of cross-reality systems. By simulating all levels of the reality-virtuality continuum entirely in Virtual Reality, our concept overcomes the asynchronicity of realities, eliminating technical obstacles. Our VRception Toolkit leverages this concept to allow rapid prototyping of cross-reality systems and easy remixing of elements from all continuum levels. We replicated six cross-reality papers using our toolkit and presented them to their authors. Interviews with them revealed that our toolkit sufficiently replicates their core functionalities and allows quick iterations. Additionally, remote participants used our toolkit in pairs to collaboratively implement prototypes in about eight minutes that they would have otherwise expected to take days.

Nowadays, deep learning models enable numerous safety-critical applications, such as biometric authentication, medical diagnosis support, and self-driving cars. However, previous studies have frequently demonstrated that these models are attackable through slight modifications of their inputs, so-called adversarial attacks. Hence, researchers proposed investigating examples of these attacks with explainable artificial intelligence to understand them better. In this line, we developed an expert tool to explore adversarial attacks and defenses against them. To demonstrate the capabilities of our visualization tool, we worked with the publicly available CIFAR-10 dataset and generated one-pixel attacks. After that, we conducted an online evaluation with 16 experts. We found that our tool is usable and practical, providing evidence that it can support understanding, explaining, and preventing adversarial examples.

Virtual Reality (VR) is becoming increasingly popular both in the entertainment and professional domains. Behavioral biometrics have recently been investigated as a means to continuously and implicitly identify users in VR. Applications in VR can specifically benefit from this, for example, to adapt virtual environments and user interfaces as well as to authenticate users. In this work, we conduct a lab study (N = 16) to explore how accurately users can be identified during two task-driven scenarios based on their spatial movement. We show that an identification accuracy of up to 90% is possible across sessions recorded on different days. Moreover, we investigate the role of users’ physiology in behavioral biometrics by virtually altering and normalizing their body proportions. We find that body normalization in general increases the identification rate, in some cases by up to 38%; hence, it improves the performance of identification systems.

We envision the human body as a platform for fast take-off and landing of drones in entertainment and professional uses such as medical emergencies, rescue missions, or supporting police units. This new interaction modality challenges our knowledge of human-drone experiences, in which interaction usually occurs at a distance from the body. This work explores important factors for understanding the interplay between drones and humans. We first investigated the suitability of various body locations for landing in an online study (N = 159). Our results, presented as body maps, show that the hand and upper back are particularly well-suited body locations. We further tested these findings in a follow-up study (N = 12), in which participants experienced drones landing on their bodies through carefully designed and pre-recorded 360°videos. This immersion into the landing scenarios helped us to identify common themes and research approaches for different body parts. Taken together, the findings provide first insights into location preferences and themes for drones landing on the human body.

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.

Virtual worlds are infinite environments in which the user can move around freely. When shifting from controller-based movement to regular walking as an input, the limitation of the real world also limits the virtual world. Tackling this challenge, we propose the use of electrical muscle stimulation to limit the necessary real-world space to create an unlimited walking experience. We thereby actuate the users` legs in a way that they deviate from their straight route and thus, walk in circles in the real world while still walking straight in the virtual world. We report on a study comparing this approach to vision shift - the state of the art approach - as well as combining both approaches. The results show that particularly combining both approaches yield high potential to create an infinite walking experience.

We present LYRA, a modular in-flight system that enhances service and assists flight attendants during their work. LYRA enables passengers to browse and order services from their smartphones. Smart glasses and a smart shoe-clip with RFID reader module provides flight attendants with situated information. We gained first insights into how flight attendants and passengers use of the system during a long distance flight from Frankfurt to Houston.

Notifications on mobile devices are a prominent source of interruptions. Previous work suggests using opportune moments to deliver notifications to reduce negative effects. In this paper, we instead explore the manual deferral of notifications. We developed an Android app that allows users to "snooze" mobile notifications for a user-defined amount of time or to a user-defined point in time. Using this app, we conducted a year-long in-the-wild study with 295 active users. To complement the findings, we recruited 16 further participants who used the app for one week and subsequently interviewed them. In both studies, snoozing was mainly used to defer notifications related to people and events. The reasons for deferral were manifold, from not being able to attend notifications immediately to not wanting to. Daily routines played an important role in the deferral of notifications. Most notifications were deferred to the same day or next morning, and a deferral of more than two days was an exception. Based on our findings, we derive design implications that can inform the design of future smart notification systems.

Applying Augmented Reality in education is being explored by many scientists. Therefore, we augment digital slides of lectures in higher education. We implemented a web server application, which allows professors to create their own AR slides. We also developed a mobile app for students to scan the slides and view the augmentation in lectures or learning sessions. To assess the usability of our system, we conducted a study with fifteen students and two professors. Students' feedback indicated that our AR app could be integrated into education. Professors, on the other hand, reported improvement suggestions. However, both groups supported applying the system in real lectures.

In this paper, we investigate the concept of gaze-based interaction with 3D user interfaces. We currently see stereo vision displays becoming ubiquitous, particularly as auto-stereoscopy enables the perception of 3D content without the use of glasses. As a result, application areas for 3D beyond entertainment in cinema or at home emerge, including work settings, mobile phones, public displays, and cars. At the same time, eye tracking is hitting the consumer market with low-cost devices. We envision eye trackers in the future to be integrated with consumer devices (laptops, mobile phones, displays), hence allowing the user's gaze to be analyzed and used as input for interactive applications. A particular challenge when applying this concept to 3D displays is that current eye trackers provide the gaze point in 2D only (x and y coordinates). In this paper, we compare the performance of two methods that use the eye's physiology for calculating the gaze point in 3D space, hence enabling gaze-based interaction with stereoscopic content. Furthermore, we provide a comparison of gaze interaction in 2D and 3D with regard to user experience and performance. Our results show that with current technology, eye tracking on stereoscopic displays is possible with similar performance as on standard 2D screens.