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The rapid advancement of the automotive industry towards automated and semi-automated vehicles has rendered traditional methods of vehicle interaction, such as touch-based and voice command systems, inadequate for a widening range of non-driving related tasks, such as referencing objects outside of the vehicle. Consequently, research has shifted toward gestural input (e.g., hand, gaze, and head pose gestures) as a more suitable mode of interaction during driving. However, due to the dynamic nature of driving and individual variation, there are significant differences in drivers' gestural input performance. While, in theory, this inherent variability could be moderated by substantial data-driven machine learning models, prevalent methodologies lean towards constrained, single-instance trained models for object referencing. These models show a limited capacity to continuously adapt to the divergent behaviors of individual drivers and the variety of driving scenarios. To address this, we propose \textit{IcRegress}, a novel regression-based incremental learning approach that adapts to changing behavior and the unique characteristics of drivers engaged in the dual task of driving and referencing objects. We suggest a more personalized and adaptable solution for multimodal gestural interfaces, employing continuous lifelong learning to enhance driver experience, safety, and convenience. Our approach was evaluated using an outside-the-vehicle object referencing use case, highlighting the superiority of the incremental learning models adapted over a single trained model across various driver traits such as handedness, driving experience, and numerous driving conditions. Finally, to facilitate reproducibility, ease deployment, and promote further research, we offer our approach as an open-source framework at \url{https://github.com/amrgomaaelhady/IcRegress}., Comment: Accepted for publication in the Proceedings of the 29th International Conference on Intelligent User Interfaces (IUI'24), March 18--21, 2024, in Greenville, SC, USA

Robotic-assisted surgical systems have demonstrated significant potential in enhancing surgical precision and minimizing human errors. However, existing systems lack the ability to accommodate the unique preferences and requirements of individual surgeons. Additionally, they primarily focus on general surgeries (e.g., laparoscopy) and are not suitable for highly precise microsurgeries, such as ophthalmic procedures. Thus, we propose a simulation-based image-guided approach for surgeon-centered autonomous agents that can adapt to the individual surgeon's skill level and preferred surgical techniques during ophthalmic cataract surgery. Our approach utilizes a simulated environment to train reinforcement and imitation learning agents guided by image data to perform all tasks of the incision phase of cataract surgery. By integrating the surgeon's actions and preferences into the training process with the surgeon-in-the-loop, our approach enables the robot to implicitly learn and adapt to the individual surgeon's unique approach through demonstrations. This results in a more intuitive and personalized surgical experience for the surgeon. Simultaneously, it ensures consistent performance for the autonomous robotic apprentice. We define and evaluate the effectiveness of our approach using our proposed metrics; and highlight the trade-off between a generic agent and a surgeon-centered adapted agent. Moreover, our approach has the potential to extend to other ophthalmic surgical procedures, opening the door to a new generation of surgeon-in-the-loop autonomous surgical robots. We provide an open-source simulation framework for future development and reproducibility.

Creating a diverse and comprehensive dataset of hand gestures for dynamic human-machine interfaces in the automotive domain can be challenging and time-consuming. To overcome this challenge, we propose using synthetic gesture datasets generated by virtual 3D models. Our framework utilizes Unreal Engine to synthesize realistic hand gestures, offering customization options and reducing the risk of overfitting. Multiple variants, including gesture speed, performance, and hand shape, are generated to improve generalizability. In addition, we simulate different camera locations and types, such as RGB, infrared, and depth cameras, without incurring additional time and cost to obtain these cameras. Experimental results demonstrate that our proposed framework, SynthoGestures\footnote{\url{https://github.com/amrgomaaelhady/SynthoGestures}}, improves gesture recognition accuracy and can replace or augment real-hand datasets. By saving time and effort in the creation of the data set, our tool accelerates the development of gesture recognition systems for automotive applications., Comment: Shorter versions are accepted as AutomotiveUI2023 Work in Progress and UIST2023 Poster Papers

Interaction with virtual objects displayed in Optical See-through Augmented Reality is still mostly done with controllers or hand gestures. A much more intuitive way of interacting with virtual content is to use physical proxy objects to interact with the virtual objects. Here, the virtual model is superimposed on a physical object, which can then be touched and moved to interact with the virtual object. Since it is not possible to use an exact replica as a tangible proxy object for every use case, we conducted a study to determine the extent to which the shape of the physical object can deviate from the shape of the virtual object without massively impacting performance and usability, as well as the sense of presence. Our study, in which we investigated different levels of abstraction for a sofa model, shows that the physical proxy object can be abstracted to a certain degree. At the same time, our results indicate that the physical object must have at least a similar shape as the virtual object in order to serve as a suitable proxy.

Shared automated mobility-on-demand promises efficient, sustainable, and flexible transportation. Nevertheless, security concerns, resilience, and their mutual influence - especially at night - will likely be the most critical barriers to public adoption since passengers have to share rides with strangers without a human driver on board. As related work points out that information about fellow travelers might mitigate passengers' concerns, we designed two user interface variants to investigate the role of this information in an exploratory within-subjects user study (N = 24). Participants experienced four automated day and night rides with varying personal information about co-passengers in a simulated environment. The results of the mixed-method study indicate that having information about other passengers (e.g., photo, gender, and name) positively affects user experience at night. In contrast, it is less necessary during the day. Considering participants' simultaneously raised privacy demands poses a substantial challenge for resilient system design.

Recent advances in machine learning models allowed robots to identify objects on a perceptual nonsymbolic level (e.g., through sensor fusion and natural language understanding). However, these primarily black-box learning models still lack interpretation and transferability and require high data and computational demand. An alternative solution is to teach a robot on both perceptual nonsymbolic and conceptual symbolic levels through hybrid neurosymbolic learning approaches with expert feedback (i.e., human-in-the-loop learning). This work proposes a concept for this user-centered hybrid learning paradigm that focuses on robotic surgical situations. While most recent research focused on hybrid learning for non-robotic and some generic robotic domains, little work focuses on surgical robotics. We survey this related research while focusing on human-in-the-loop surgical robotic systems. This evaluation highlights the most prominent solutions for autonomous surgical robots and the challenges surgeons face when interacting with these systems. Finally, we envision possible ways to address these challenges using online apprenticeship learning based on implicit and explicit feedback from expert surgeons.

Achievement goals are frequently used to support behavior change. However, they are often not specifically designed for this purpose nor account for the degree to which a user is already intending to perform the target behavior. In this paper, we investigate the perceived persuasiveness of different goal types as defined by the 3x2 Achievement Goal Model, what people like and dislike about them and the role that behavior change intentions play when aiming at increasing step counts. We created visualizations for each goal type based on a qualitative pre-study (N=18) and ensured their comprehensibility (N=18). In an online experiment (N=118), we show that there are differences in the perception of these goal types and that behavior change intentions should be considered to maximize their persuasiveness as goals evolve. Next, we derive design guidelines on when to use which type of achievement goal and what to consider when using them

Gamification is frequently used to motivate people getting more physically active. However, most systems follow a one-size-fits-all gamification approach, although past research has shown that interpersonal differences exist in the perception of gamification elements. Also, most studies investigating the effects of gamification are rather short, although it has been shown that gamification can suffer from novelty effects. In this paper, we address both these issues by investigating whether gamification elements, integrated into a fitness course booking system, have an effect on how frequently users participate in fitness courses in a gym (N=52) over a duration of 275 days (548 days including baseline). Also, the gamification elements that we implemented are tailored to specific Hexad user types, which allows us to investigate whether using suitable gamification elements leads to an increased course participation. Our results show that gamification increased the participation in fitness courses significantly and that users who received a suitable set of gamification elements - according to their Hexad user type - increased their participation significantly more than others.

Measure user experience in MR (i.e., AR/VR) user studies is essential. Researchers apply a wide range of measuring methods using objective (e.g., biosignals, time logging), behavioral (e.g., gaze direction, movement amplitude), and subjective (e.g., standardized questionnaires) metrics. Many of these measurement instruments were adapted from use-cases outside of MR but have not been validated for usage in MR experiments. However, researchers are faced with various challenges and design alternatives when measuring immersive experiences. These challenges become even more diverse when running out-of-the lab studies. Measurement methods of VR experience recently received much attention. For example, research has started embedding questionnaires in the VE for various applications, allowing users to stay closer to the ongoing experience while filling out the survey. However, there is a diversity in the interaction methods and practices on how the assessment procedure is conducted. This diversity in methods underlines a missing shared agreement of standardized measurement tools for VR experiences. AR research strongly orients on the research methods from VR, e.g., using the same type of subjective questionnaires. However, some crucial technical differences require careful considerations during the evaluation. This workshop at CHI 2021 provides a foundation to exchange expertise and address challenges and opportunities of research methods in MR user studies. By this, our workshop launches a discussion of research methods that should lead to standardizing assessment methods in MR user studies. The outcomes of the workshop will be aggregated into a collective special issue journal article., Comment: Workshop proposal at CHI '21

Current advances in machine translation increase the need for translators to switch from traditional translation to post-editing of machine-translated text, a process that saves time and improves quality. Human and artificial intelligence need to be integrated in an efficient way to leverage the advantages of both for the translation task. This paper outlines approaches at this boundary of AI and HCI and discusses open research questions to further advance the field.

Cognitive factors such as distance-and speed perception play an important role when it comes to human performance during bodily exercise. Especially for bike training, deception of distance and speed can have a positive influence in one's performance and add to effective training. In this paper we investigate the performance of participants exposed to speed deception in virtual reality environments controlled by a training bike. With DeceptiBike we created a bike simulator that allows to manipulate speed perception via visual-and haptic cues. Our results show that we effectively can increase the users speed by 15.2% without the user noticing the effect. Our findings highlight the possibility of speed deception as a method for novel bike training systems.

Cognitive factors such as distance-and speed perception play an important role when it comes to human performance during bodily exercise. Especially for bike training, deception of distance and speed can have a positive influence in one's performance and add to effective training. In this paper we investigate the performance of participants exposed to speed deception in virtual reality environments controlled by a training bike. With DeceptiBike we created a bike simulator that allows to manipulate speed perception via visual-and haptic cues. Our results show that we effectively can increase the users speed by 15.2% without the user noticing the effect. Our findings highlight the possibility of speed deception as a method for novel bike training systems.

The Position Based Fluids (PBF) method is a state-of-the-art approach for fluid simulations in the context of real-time applications like games. It uses an iterative solver concept that tries to maintain a constant fluid density (incompressibility) to realize incompressible fluids like water. However, larger fluid volumes that consist of several hundred thousand particles (e.g. for the simulation of oceans) require many iterations and a lot of simulation power. We present a lightweight and easy-to-integrate extension to PBF that adaptively adjusts the number of solver iterations on a fine-grained basis. Using a novel adaptive-simulation approach, we are able to achieve significant improvements in performance on our evaluation scenarios while maintaining high-quality results in terms of visualization quality, which makes it a perfect choice for game developers. Furthermore, our method does not weaken the advantages of prior work and seamlessly integrates into other position-based methods for physically-based simulations., Comment: 16 pages, International Journal of Computer Graphics & Animation Vol.6, No.3, July 2016

We present a mobile crowdsourcing study to capture and examine the nightlife patterns of two youth populations in Switzerland. Our contributions are three fold. First, we developed a smartphone application to capture data on places, social context and nightlife activities, and to record mobile videos capturing the ambiance of places. Second, we conducted an “in-the-wild” study with more than 200 participants over a period of three months in two Swiss cities, resulting in a total of 1,394 unique place visits and 843 videos that spread across place categories (including personal homes and public parks), social and ambiance variables. Finally, we investigated the use of automatic ambiance features to estimate the loudness and brightness of places at scale, and found that while features are reliable with respect to video content, videos do not always reflect the place ambiance reported by people in-situ. We believe that the developed methodology provides an opportunity to understand the physical mobility, activities, and social context of youth as they experience different aspects of nightlife.

Mobile gaze-based interaction with multiple displays may occur from arbitrary positions and orientations. However, maintaining high gaze estimation accuracy in such situations remains a significant challenge. In this paper, we present GazeProjector, a system that combines (1) natural feature tracking on displays to determine the mobile eye tracker?s position relative to a display with (2) accurate point-of-gaze estimation. GazeProjector allows for seamless gaze estimation and interaction on multiple displays of arbitrary sizes independently of the user?s position and orientation to the display. In a user study with 12 participants we compare GazeProjector to established methods (here: visual on-screen markers and a state-of-the-art video-based motion capture system). We show that our approach is robust to varying head poses, orientations, and distances to the display, while still providing high gaze estimation accuracy across multiple displays without re-calibration for each variation. Our system represents an important step towards the vision of pervasive gaze-based interfaces.

Often, we operate mobile devices using only one hand. The hand thereby serves two purposes: holding the device and operating the touch screen with the thumb. The current trend of increasing screen sizes however, makes it close to impossible to reach all parts of the screen (especially the top area) for users with average hand sizes. One solution is to offer adaptive user interfaces for such one-handed interactions. These modes have to be triggered manually and thus induce a critical overhead. They are further designed to bring all content closer, regardless of whether the phone is operated with the left or right hand. In this paper, we present an algorithm that allows determining the users' interacting hand from their unlocking behavior. Our algorithm correctly distinguishes one- and twohanded usage as well as left- and right handed unlocking in 98.51% of all cases. This is achieved through a k-nearest neighbor comparison of the internal sensor readings of the smartphone during the unlocking process.

Eye movement analysis can provide insights into the cognitive processes in human mind and have been successfully utilized to study visual tasks such as reading and exploration of digital displays. However recording eye movements requires costly equipment and the face-to-face individual data collection forces us to work with only a limited number of participants. Interactive displays are alternatively evaluated through mouse movements which can be collected considerably easier than eye movements. It is however an open question if and how these two types of movement are linked. In this project, we study the link between eye and mouse movements to understand the eye-hand coordination specifically with visual search tasks in geographic displays.

We present a cross-validation approach to assess animations of movement data. Specifically, we investigate if and how display design, data complexity and user background and training might influence participants’ decision-making with animated designs. Our triangulation approach is based on eye-tracking records, galvanic skin conductance responses, and electroencephalography data. We raise data analysis issues and data synchronization challenges for discussion at the workshop relating to data integration at various resolutions. With this empirical triangulation approach, we hope to better understand user decision-making with animated displays, and aim to develop sound animation design guidelines.

A key issue with state-of-the-art mobile eye trackers, particularly during long-term recordings in daily life, is the need for cumbersome and time consuming (re)calibration. To reduce this burden, in this paper we investigate the feasibility of adapting the calibration obtained for one user to another. Calibration adaptation is automatically performed using a light-weight linear translation. We compare three different methods to compute the translation: "multi-point", where all calibration-points are used, "1-point", and "0-point" that uses only an external parameter. We evaluate these methods in a 6-participant user study in a controlled laboratory setting by measuring the error in visual angle between the predicted gaze point and the true gaze point. Our results show that, averaged across all participants, the best adapted calibration is only 0.8° (mean) off the calibration obtained for that specific user. We also show the potential of the 1-point and 0-point methods compared to the time-consuming multi-point computation.

This paper presents two novel handheld projector systems for indoor pervasive computing spaces. These projection-based devices are “aware” of their environment in ways not demonstrated previously. They offer both spatial awareness, where the system infers location and orientation of the device in 3D space, and geometry awareness, where the system constructs the 3D structure of the world around it, which can encompass the user as well as other physical objects, such as furniture and walls. Previous work in this area has predominantly focused on infrastructure-based spatial-aware handheld projection and interaction. Our prototypes offer greater levels of environment awareness, but achieve this using two opposing approaches; the first infrastructure-based and the other infrastructure-less sensing. We highlight a series of interactions including direct touch, as well as in-air gestures, which leverage the shadow of the user for interaction. We describe the technical challenges in realizing these novel systems; and compare them directly by quantifying their location tracking and input sensing capabilities.

Previous work in eco-feedback has focused either on new sensing technologies, or on people’s responses to specific feedback devices and other interventions placed in their homes. Complementary to such work, we take a two-pronged approach in accounting for both the amount of resources that specific appliances draw upon, and how the services provided by such appliances tie into everyday life. We performed a study in four student flats over a twenty-day period, collecting data using interviews with eleven participants and over two hundred in-home sensors. Our goal is to understand the challenges in accounting for re- sources, services and practices at home, and what these challenges mean for future sustainability and eco-feedback research.

This paper presents two novel handheld projector systems for indoor pervasive computing spaces. These projection-based devices are “aware” of their environment in ways not demonstrated previously. They offer both spatial awareness, where the system infers location and orientation of the device in 3D space, and geometry awareness, where the system constructs the 3D structure of the world around it, which can encompass the user as well as other physical objects, such as furniture and walls. Previous work in this area has predominantly focused on infrastructure-based spatial-aware handheld projection and interaction. Our prototypes offer greater levels of environment awareness, but achieve this using two opposing approaches; the first infrastructure-based and the other infrastructure-less sensing. We highlight a series of interactions including direct touch, as well as in-air gestures, which leverage the shadow of the user for interaction. We describe the technical challenges in realizing these novel systems; and compare them directly by quantifying their location tracking and input sensing capabilities.

A key issue with state-of-the-art mobile eye trackers, particularly during long-term recordings in daily life, is the need for cumbersome and time consuming (re)calibration. To reduce this burden, in this paper we investigate the feasibility of adapting the calibration obtained for one user to another. Calibration adaptation is automatically performed using a light-weight linear translation. We compare three different methods to compute the translation: "multi-point", where all calibration-points are used, "1-point", and "0-point" that uses only an external parameter. We evaluate these methods in a 6-participant user study in a controlled laboratory setting by measuring the error in visual angle between the predicted gaze point and the true gaze point. Our results show that, averaged across all participants, the best adapted calibration is only 0.8° (mean) off the calibration obtained for that specific user. We also show the potential of the 1-point and 0-point methods compared to the time-consuming multi-point computation.

Previous work in eco-feedback has focused either on new sensing technologies, or on people’s responses to specific feedback devices and other interventions placed in their homes. Complementary to such work, we take a two-pronged approach in accounting for both the amount of resources that specific appliances draw upon, and how the services provided by such appliances tie into everyday life. We performed a study in four student flats over a twenty-day period, collecting data using interviews with eleven participants and over two hundred in-home sensors. Our goal is to understand the challenges in accounting for re- sources, services and practices at home, and what these challenges mean for future sustainability and eco-feedback research.

In recent years interactive visualization of 3D data has become important and widespread due to the requirements of several application areas. However, current user interfaces often lack adequate support for 3D interactions: 2D desktop systems are often limited in cases where natural interaction with 3D content is required, and 3D user interfaces consisting of stereoscopic projections and tracked input devices are rarely adopted by ordinary users. Touch interaction has received considerable attention for 2D interfaces, and more recently for 3D interfaces. Many touch devices now support multiple degrees of freedom input by capturing multiple 2D contact positions on the surface as well as varying levels of pressure and even depth. There is great potential for multi-touch interfaces to provide the traditionally difficult to achieve combination of natural 3D interaction without any instrumentation. When combined with a stereoscopic display as well as depth cameras, we believe that multi-touch technology can form the basis for a next generation of 3D user interfaces. Several research groups have begun to explore the potential, limitations, and challenges of this and other 3D touch environments, and first commercial systems are already available. The goal of the seminar "Touching the 3rd Dimension (T3D)" is to address the research and industrial challenges involved in exploring the space where the flat digital world of surface computing meets the physical, spatially complex, 3D space in which we live. The seminar will provide a common forum to attract groups of conference attendees who share their visions of the future and recent results in the area of improving 3D interaction and visualization by taking advantage of the strengths of advanced multi-touch computing.

We assessed age-related differences in adults in familiarization to treadmill walking within virtual environments (VE), and examined whether treadmill walking after familiarization resembles overground walking. Seventeen younger and 17 older adults walked at preferred speed on an overground walkway and afterwards walked at the same speed for 20 min on a treadmill coupled to a VE. A motion capture system was used to measure spatio-temporal gait parameters. On the treadmill, both younger and older adults initially displayed decreased step length and increased step width, cadence, and time in double support relative to overground walking. Except for time in double support, step characteristics approached overground walking-behavior with a negatively accelerated trend. After 15 min of treadmill walking, changes became minor corresponding to less than 1% deviations to individuals' overground walking. At the end of familiarization, average differences in step length, cadence, and double support relative to overground walking were reduced to less than 5 percent in both age groups. For step width, younger adults approximated overground walking after 20 min more closely than older adults, probably reflecting larger initial differences between treadmill and overground walking among older adults. We conclude (a) that 20 min of familiarization to treadmill walking in a VE are sufficient to reach stable walking patterns resembling those observed in overground walking, but that some differences between the two settings remain, especially in older adults; (b) that sufficient familiarization to the treadmill is needed to ascertain the validity and generalizability of comparisons between younger and older adults.

This Dagstuhl seminar has focused on bringing together researchers from a diverse set of fields of Computer Science to discuss the next generation of pervasive public display environments. The state-of-the-art in software control of display environments is best represented by commercial products that enable advance scheduling of content on a network of displays. Essentially such systems offer a traditional broadcast model based on linear playout of content and offer no support for user recognition or interaction with displays. Other display environments, e.g., in offices or conference centres, might simply run single, isolated applications, such as video conferencing or video players. In addition, current systems typically function as small isolated networks consisting of a limited number of displays under a single management domain (e.g. in a single shopping centre). In this respect, a parallel can be drawn with the state of computing prior to the invention of the Internet - machines were networked together in small clusters to facilitate resource sharing, control and communication but there were no mechanisms for interconnecting these networks.

In many mid- to large-sized cities public maps are ubiquitous. One can also find a great number of maps in parks or near hiking trails. Public maps help to facilitate orientation and provide special information to not only tourists but also to locals who just want to look up an unfamiliar place while on the go. These maps offer many advantages compared to mobile maps from services like Google Maps Mobile or Nokia Maps. They often show local landmarks and sights that are not shown on standard digital maps. Often these 'You are here' (YAH) maps are adapted to a special use case, e.g. a zoo map or a hiking map of a certain area. Being designed for a fashioned purpose these maps are often aesthetically well designed and their usage is therefore more pleasant. In this paper we present a novel technique and application called PhotoMap that uses images of 'You are here' maps taken with a GPS-enhanced mobile camera phone as background maps for on-the-fly navigation tasks. We discuss different implementations of the main challenge, namely helping the user to properly georeference the taken image with sufficient accuracy to support pedestrian navigation tasks. We present a study that discusses the suitability of various public maps for this task and we evaluate if these georeferenced photos can be used for navigation on GPS-enabled devices.

Public displays and mobile phones are ubiquitous technologies that are already weaving themselves into the everyday life of urban citizens. The combination of the two enables new and novel possibilities, such as interaction with displays that are not physically accessible, extending screen real estate for mobile phones or transferring user content to and from public displays. However, current usability evaluations of prototype systems have explored only a small part of this design space, as usage of such systems is deeply embedded in and dependent on social and everyday context. In order to investigate issues surrounding appropriation and real use in social context field studies are necessary. In this paper we present our experiences with field deployments in a continuum between exploratory prototypes and technology probes. We present benefits and drawbacks of different evaluation methods, and provide a number of validated lessons from our deployments.

In many mid- to large-sized cities public maps are ubiquitous. One can also find a great number of maps in parks or near hiking trails. Public maps help to facilitate orientation and provide special information to not only tourists but also to locals who just want to look up an unfamiliar place while on the go. These maps offer many advantages compared to mobile maps from services like Google Maps Mobile or Nokia Maps. They often show local landmarks and sights that are not shown on standard digital maps. Often these 'You are here' (YAH) maps are adapted to a special use case, e.g. a zoo map or a hiking map of a certain area. Being designed for a fashioned purpose these maps are often aesthetically well designed and their usage is therefore more pleasant. In this paper we present a novel technique and application called PhotoMap that uses images of 'You are here' maps taken with a GPS-enhanced mobile camera phone as background maps for on-the-fly navigation tasks. We discuss different implementations of the main challenge, namely helping the user to properly georeference the taken image with sufficient accuracy to support pedestrian navigation tasks. We present a study that discusses the suitability of various public maps for this task and we evaluate if these georeferenced photos can be used for navigation on GPS-enabled devices.

Public displays and mobile phones are ubiquitous technologies that are already weaving themselves into the everyday life of urban citizens. The combination of the two enables new and novel possibilities, such as interaction with displays that are not physically accessible, extending screen real estate for mobile phones or transferring user content to and from public displays. However, current usability evaluations of prototype systems have explored only a small part of this design space, as usage of such systems is deeply embedded in and dependent on social and everyday context. In order to investigate issues surrounding appropriation and real use in social context field studies are necessary. In this paper we present our experiences with field deployments in a continuum between exploratory prototypes and technology probes. We present benefits and drawbacks of different evaluation methods, and provide a number of validated lessons from our deployments.

In current mobile navigation systems users receive the navigational instructions on a visual display or by descriptive audio. The mapping between the provided navigation information and the surrounding world has still to be performed by the users. In our approach that aims at public spaces, we combine a public display that shows directions with a synchronized output on a personal device. We describe a system where on the public display a compass with a rotating needle is shown. When the compass needle points in the desired direction, the mobile device of the user vibrates. This unobtrusive cue, allows the user to navigate without listening to or looking at the mobile device. In this paper we introduce the concept of synchronized information displays for navigation. We describe our prototype of such a system and report on a user study, that shows the feasibility of the approach.

In this paper, we describe a public navigation system which uses adaptive displays as directional signs. The displays are mounted to walls where they provide passersbys with directional information. Each sign is an autonomous, wirelessly networked digital displays connected to a central server. The signs are position-aware and able to adapt their display content in accordance with their current position. Advantages of such a navigation system include improved flexibility, dynamic adaptation and ease of setup and maintenance.

In current mobile navigation systems users receive the navigational instructions on a visual display or by descriptive audio. The mapping between the provided navigation information and the surrounding world has still to be performed by the users. In our approach that aims at public spaces, we combine a public display that shows directions with a synchronized output on a personal device. We describe a system where on the public display a compass with a rotating needle is shown. When the compass needle points in the desired direction, the mobile device of the user vibrates. This unobtrusive cue, allows the user to navigate without listening to or looking at the mobile device. In this paper we introduce the concept of synchronized information displays for navigation. We describe our prototype of such a system and report on a user study, that shows the feasibility of the approach.

In this paper, we describe a public navigation system which uses adaptive displays as directional signs. The displays are mounted to walls where they provide passersbys with directional information. Each sign is an autonomous, wirelessly networked digital displays connected to a central server. The signs are position-aware and able to adapt their display content in accordance with their current position. Advantages of such a navigation system include improved flexibility, dynamic adaptation and ease of setup and maintenance.