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Matthias Hoppe

Publications and source records attributed to Matthias Hoppe.

7 recordsLinked to original sources

JSL-DC: A Word-Level Japanese Sign Language Dataset with Linguist-Derived Descriptions for Distinguishing Confusable Signs

Effective sign language (SL) acquisition is crucial for deaf children, yet 95% are born to hearing parents who often lack proficiency in SL. SL recognition can power learning tools to help parents communicate with their children. However, Japanese Sign Language (JSL) lacks large-scale, multi-signer datasets, hindering the development of models that can generalize to new users. To address this gap, we introduce JSL-DC, the largest JSL dataset by video count, comprising 36.7K videos from 19 signers. The entire process was Deaf-centric: the lexicon comprising 270 JSL words was selected by Deaf and Coda linguists to facilitate parent-child communication, all participants were Deaf individuals who use JSL daily, and the data underwent a two-stage review process involving Deaf linguists. Moreover, we provide linguist-derived descriptions for distinguishing confusable signs. We demonstrate that the proposed model inspired by the descriptions outperforms state-of-the-art recognition methods by 9.8% on the confusable subset. The dataset, along with its linguistic description that inspires new models, will be released under a CC-BY 4.0 license to accelerate research in SL recognition.

cs.CV

Abstraction Beats Realism: Physiological Visualizations Enhance Arousal Synchrony in VR Concert Recreations

Live cultural experiences like concerts generate shared physiological arousal among audience members, a collective resonance that contributes to their emotional power. Recreating such experiences in virtual reality therefore requires not just audiovisual fidelity, but reproduction of this physiological dimension. Yet current VR evaluation methods rely on post-hoc self-reports that interrupt immersion and cannot capture moment-to-moment arousal dynamics. We propose cross-temporal physiological synchrony as an unobtrusive methodology for evaluating VR cultural recreations: measuring how closely a VR participant's arousal patterns align with those of the original live audience. In a two-phase study, we recorded electrodermal activity from 40 live concert attendees, then created three VR recreations with varying abstraction levels (realistic 360-degree video, mixed video-plus-visualization, and fully abstract physiological representations) and measured synchrony with 22 laboratory participants using Dynamic Time Warping. Contrary to assumptions favoring realism, abstract visualizations achieved the strongest synchrony with live audiences. During musical climaxes, the abstract condition maintained correlation while realistic video showed none. These findings suggest that abstract physiological representations may be more effective than realistic footage for evoking authentic collective engagement in VR cultural recreations.

cs.HC

Cuddle-Fish: Exploring a Soft Floating Robot with Flapping Wings for Physical Interactions

Flying robots, such as quadrotor drones, offer new possibilities for human-robot interaction but often pose safety risks due to fast-spinning propellers, rigid structures, and noise. In contrast, lighter-than-air flapping-wing robots, inspired by animal movement, offer a soft, quiet, and touch-safe alternative. Building on these advantages, we present Cuddle-Fish, a soft flapping-wing floating robot designed for close-proximity interactions in indoor spaces. Through a user study with 24 participants, we explored their perceptions of the robot and experiences during a series of co-located demonstrations in which the robot moved near them. Results showed that participants felt safe, willingly engaged in touch-based interactions with the robot, and exhibited spontaneous affective behaviours, such as patting, stroking, hugging, and cheek-touching, without external prompting. They also reported positive emotional responses towards the robot. These findings suggest that the soft floating robot with flapping wings can serve as a novel and socially acceptable alternative to traditional rigid flying robots, opening new potential for applications in companionship, affective interaction, and play in everyday indoor environments.

cs.HC

Haptic Empathy: Investigating Individual Differences in Affective Haptic Communications

Nowadays, touch remains essential for emotional conveyance and interpersonal communication as more interactions are mediated remotely. While many studies have discussed the effectiveness of using haptics to communicate emotions, incorporating affect into haptic design still faces challenges due to individual user tactile acuity and preferences. We assessed the conveying of emotions using a two-channel haptic display, emphasizing individual differences. First, 24 participants generated 187 haptic messages reflecting their immediate sentiments after watching 8 emotionally charged film clips. Afterwards, 19 participants were asked to identify emotions from haptic messages designed by themselves and others, yielding 593 samples. Our findings suggest potential links between haptic message decoding ability and emotional traits, particularly Emotional Competence (EC) and Affect Intensity Measure (AIM). Additionally, qualitative analysis revealed three strategies participants used to create touch messages: perceptive, empathetic, and metaphorical expression.

cs.HC

The AI Ghostwriter Effect: When Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors

Human-AI interaction in text production increases complexity in authorship. In two empirical studies (n1 = 30 & n2 = 96), we investigate authorship and ownership in human-AI collaboration for personalized language generation. We show an AI Ghostwriter Effect: Users do not consider themselves the owners and authors of AI-generated text but refrain from publicly declaring AI authorship. Personalization of AI-generated texts did not impact the AI Ghostwriter Effect, and higher levels of participants' influence on texts increased their sense of ownership. Participants were more likely to attribute ownership to supposedly human ghostwriters than AI ghostwriters, resulting in a higher ownership-authorship discrepancy for human ghostwriters. Rationalizations for authorship in AI ghostwriters and human ghostwriters were similar. We discuss how our findings relate to psychological ownership and human-AI interaction to lay the foundations for adapting authorship frameworks and user interfaces in AI in text-generation tasks.

cs.HC

Remote VR Studies -- A Framework for Running Virtual Reality Studies Remotely Via Participant-Owned HMDs

We investigate the opportunities and challenges of running virtual reality (VR) studies remotely. Today, many consumers own head-mounted displays (HMDs), allowing them to participate in scientific studies from their homes using their own equipment. Researchers can benefit from this approach by being able to reach a more diverse study population and to conduct research at times when it is difficult to get people into the lab (cf. the COVID pandemic). We first conducted an online survey (N=227), assessing HMD owners' demographics, their VR setups, and their attitudes towards remote participation. We then identified different approaches to running remote studies and conducted two case studies for an in-depth understanding. We synthesize our findings into a framework for remote VR studies, discuss the strengths and weaknesses of the different approaches, and derive best practices. Our work is valuable for HCI researchers conducting VR studies outside labs.

cs.HC

Don't Drone Yourself in Work: Discussing DronOS as a Framework for Human-Drone Interaction

More and more off-the-shelf drones provide frameworks that enable the programming of flight paths. These frameworks provide vendor-dependent programming and communication interfaces that are intended for flight path definitions. However, they are often limited to outdoor and GPS-based use only. A key disadvantage of such a solution is that they are complicated to use and require readjustments when changing the drone model. This is time-consuming since it requires redefining the flight path for the new framework. This workshop paper proposes additional features for DronOS, a community-driven framework that enables model-independent automatisation and programming of drones. We enhanced DronOS to include additional functions to account for the specific design constraints in human-drone-interaction. This paper provides a starting point for discussing the requirements involved in designing a drone system with other researchers within the human-drone interaction community. We envision DronOS as a community-driven framework that can be applied to generic drone models, hence enabling the automatisation for any commercially available drone. Our goal is to build DronOS as a software tool that can be easily used by researchers and practitioners to prototype novel drone-based systems.

cs.HC