Person: Reiterer, Harald
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Relaxed forced choice improves performance of visual quality assessment methods
In image quality assessment, a collective visual quality score for an image or video is obtained from the individual ratings of many subjects. One commonly used format for these experiments is the two-alternative forced choice method. Two stimuli with the same content but differing visual quality are presented sequentially or side-by-side. Subjects are asked to select the one of better quality, and when uncertain, they are required to guess. The relaxed alternative forced choice format aims to reduce the cognitive load and the noise in the responses due to the guessing by providing a third response option, namely, ``not sure''. This work presents a large and comprehensive crowdsourcing experiment to compare these two response formats: the one with the ``not sure'' option and the one without it. To provide unambiguous ground truth for quality evaluation, subjects were shown pairs of images with differing numbers of dots and asked each time to choose the one with more dots. Our crowdsourcing study involved 254 participants and was conducted using a within-subject design. Each participant was asked to respond to 40 pair comparisons with and without the ``not sure'' response option and completed a questionnaire to evaluate their cognitive load for each testing condition. The experimental results show that the inclusion of the ``not sure'' response option in the forced choice method reduced mental load and led to models with better data fit and correspondence to ground truth. We also tested for the equivalence of the models and found that they were different. The dataset is available at http://database.mmsp-kn.de/cogvqa-database.html.
A Survey on Measuring Cognitive Workload in Human-Computer Interaction
The ever-increasing number of computing devices around us results in more and more systems competing for our attention, making cognitive workload a crucial factor for the user experience of human-computer interfaces. Research in Human-Computer Interaction (HCI) has used various metrics to determine users’ mental demands. However, there needs to be a systematic way to choose an appropriate and effective measure for cognitive workload in experimental setups, posing a challenge to their reproducibility. We present a literature survey of past and current metrics for cognitive workload used throughout HCI literature to address this challenge. By initially exploring what cognitive workload resembles in the HCI context, we derive a categorization supporting researchers and practitioners in selecting cognitive workload metrics for system design and evaluation. We conclude with three following research gaps: (1) defining and interpreting cognitive workload in HCI, (2) the hidden cost of the NASA-TLX, and (3) HCI research as a catalyst for workload-aware systems, highlighting that HCI research has to deepen and conceptualize the understanding of cognitive workload in the context of interactive computing systems.
Adapting visualizations and interfaces to the user
Adaptive visualization and interfaces pervade our everyday tasks to improve interaction from the point of view of user performance and experience. This approach allows using several user inputs, whether physiological, behavioral, qualitative, or multimodal combinations, to enhance the interaction. Due to the multitude of approaches, we outline the current research trends of inputs used to adapt visualizations and user interfaces. Moreover, we discuss methodological approaches used in mixed reality, physiological computing, visual analytics, and proficiency-aware systems. With this work, we provide an overview of the current research in adaptive systems.
Human–Computer Integration : towards Integrating the Human Body with the Computational Machine
Human-Computer Integration (HInt) is an emerging new paradigm in the human-computer interaction (HCI) field. Its goal is to integrate the human body and the computational machine. This monograph presents two key dimensions of Human-Computer Integration (bodily agency and bodily ownership) and proposes a set of challenges that we believe need to be resolved in order to bring the paradigm forward. Ultimately, our work aims to facilitate a more structured investigation into human body and computational machine integration.
ARound the Smartphone: Investigating the Efects of Virtually-Extended Display Size on Spatial Memory
Smartphones conveniently place large information spaces in the palms of our hands. While research has shown that larger screens positively affect spatial memory, workload, and user experience, smartphones remain fairly compact for the sake of device ergonomics and portability. Thus, we investigate the use of hybrid user interfaces to virtually increase the available display size by complementing the smartphone with an augmented reality head-worn display. We thereby combine the benefts of familiar touch interaction with the near-infnite visual display space aforded by augmented reality. To better understand the potential of virtually-extended displays and the possible issues of splitting the user’s visual attention between two screens (real and virtual), we conducted a within-subjects experiment with 24 participants completing navigation tasks using diferent virtually-augmented display sizes. Our findings reveal that a desktop monitor size represents a “sweet spot” for extending smartphones with augmented reality, informing the design of hybrid user interfaces.
MoPeDT : A Modular Head-Mounted Display Toolkit to Conduct Peripheral Vision Research
Peripheral vision plays a significant role in human perception and orientation. However, its relevance for human-computer interaction, especially head-mounted displays, has not been fully explored yet. In the past, a few specialized appliances were developed to display visual cues in the periphery, each designed for a single specific use case only. A multi-purpose headset to exclusively augment peripheral vision did not exist yet. We introduce MoPeDT: Modular Peripheral Display Toolkit, a freely available, flexible, reconfigurable, and extendable headset to conduct peripheral vision research. MoPeDT can be built with a 3D printer and off-the-shelf components. It features multiple spatially configurable near-eye display modules and full 3D tracking inside and outside the lab. With our system, researchers and designers may easily develop and prototype novel peripheral vision interaction and visualization techniques. We demonstrate the versatility of our headset with several possible applications for spatial awareness, balance, interaction, feedback, and notifications. We conducted a small study to evaluate the usability of the system. We found that participants were largely not irritated by the peripheral cues, but the headset's comfort could be further improved. We also evaluated our system based on established heuristics for human-computer interaction toolkits to show how MoPeDT adapts to changing requirements, lowers the entry barrier for peripheral vision research, and facilitates expressive power in the combination of modular building blocks.
Re-locations : Augmenting Personal and Shared Workspaces to Support Remote Collaboration in Incongruent Spaces
Augmented reality (AR) can create the illusion of being virtually co-located during remote collaboration, e.g., by visualizing remote co-workers as avatars. However, spatial awareness of each other’s activities is limited as physical spaces, including the position of physical devices, are often incongruent. Therefore, alignment methods are needed to support activities on physical devices. In this paper, we present the concept of Re-locations, a method for enabling remote collaboration with augmented reality in incongruent spaces. The idea of the concept is to enrich remote collaboration activities on multiple physical devices with attributes of co-located collaboration such as spatial awareness and spatial referencing by locally relocating remote user representations to user-defined workspaces. We evaluated the Re-locations concept in an explorative user study with dyads using an authentic, collaborative task. Our findings indicate that Re-locations introduce attributes of co-located collaboration like spatial awareness and social presence. Based on our findings, we provide implications for future research and design of remote collaboration systems using AR.
ARound the Smartphone : Investigating the Effects of Virtually-Extended Display Size on Spatial Memory
Smartphones conveniently place large information spaces in the palms of our hands. While research has shown that larger screens positively affect spatial memory, workload, and user experience, smartphones remain fairly compact for the sake of device ergonomics and portability. Thus, we investigate the use of hybrid user interfaces to virtually increase the available display size by complementing the smartphone with an augmented reality head-worn display. We thereby combine the benefts of familiar touch interaction with the near-infnite visual display space afforded by augmented reality. To better understand the potential of virtually-extended displays and the possible issues of splitting the user’s visual attention between two screens (real and virtual), we conducted a within-subjects experiment with 24 participants completing navigation tasks using diferent virtually-augmented display sizes. Our findings reveal that a desktop monitor size represents a “sweet spot” for extending smartphones with augmented reality, informing the design of hybrid user interfaces.
Understanding and Creating Spatial Interactions with Distant Displays Enabled by Unmodified Off-The-Shelf Smartphones
Over decades, many researchers developed complex in-lab systems with the overall goal to track multiple body parts of the user for a richer and more powerful 2D/3D interaction with a distant display. In this work, we introduce a novel smartphone-based tracking approach that eliminates the need for complex tracking systems. Relying on simultaneous usage of the front and rear smartphone cameras, our solution enables rich spatial interactions with distant displays by combining touch input with hand-gesture input, body and head motion, as well as eye-gaze input. In this paper, we firstly present a taxonomy for classifying distant display interactions, providing an overview of enabling technologies, input modalities, and interaction techniques, spanning from 2D to 3D interactions. Further, we provide more details about our implementation—using off-the-shelf smartphones. Finally, we validate our system in a user study by a variety of 2D and 3D multimodal interaction techniques, including input refinement.
Arrow, Bézier Curve, or Halos? : Comparing 3D Out-of-View Object Visualization Techniques for Handheld Augmented Reality
Handheld augmented reality (AR) applications allow users to interact with their virtually augmented environment on the screen of their tablet or smartphone by simply pointing its camera at nearby objects or “points of interest” (POIs). However, this often requires users to carefully scan their surroundings in search of POIs that are out of view. Proposed 2D guides for out-of-view POIs can, unfortunately, be ambiguous due to the projection of a 3D position to 2D screen space. We address this by using 3D visualizations that directly encode the POI’s 3D direction and distance. Based on related work, we implemented three such visualization techniques: (1) 3D Arrow, (2) 3D Bézier Curve, and (3) 3D Halos. We confirmed the applicability of these three techniques in a case study and then compared them in a user study, evaluating performance, workload, and user experience. Participants performed best using 3D Arrow, while surprisingly, 3D Halos led to poor results. We discuss the design implications of these results that can inform future 3D out-of-view object visualization techniques.