64 research outputs found

    Converting Biomechanical Models from OpenSim to MuJoCo

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    OpenSim is a widely used biomechanics simulator with several anatomically accurate human musculo-skeletal models. While OpenSim provides useful tools to analyse human movement, it is not fast enough to be routinely used for emerging research directions, e.g., learning and simulating motor control through deep neural networks and Reinforcement Learning (RL). We propose a framework for converting OpenSim models to MuJoCo, the de facto simulator in machine learning research, which itself lacks accurate musculo-skeletal human models. We show that with a few simple approximations of anatomical details, an OpenSim model can be automatically converted to a MuJoCo version that runs up to 600 times faster. We also demonstrate an approach to computationally optimize MuJoCo model parameters so that forward simulations of both simulators produce similar results.Comment: Submitted to 5th International Conference on NeuroRehabilitation (ICNR2020

    "An Adapt-or-Die Type of Situation": Perception, Adoption, and Use of Text-To-Image-Generation AI by Game Industry Professionals

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    Text-to-image generation (TTIG) models, a recent addition to creative AI, can generate images based on a text description. These models have begun to rival the work of professional creatives, and sparked discussions on the future of creative work, loss of jobs, and copyright issues, amongst other important implications. To support the sustainable adoption of TTIG, we must provide rich, reliable and transparent insights into how professionals perceive, adopt and use TTIG. Crucially though, the public debate is shallow, narrow and lacking transparency, while academic work has focused on studying the use of TTIG in a general artist population, but not on the perceptions and attitudes of professionals in a specific industry. In this paper, we contribute a qualitative, exploratory interview study on TTIG in the Finnish videogame industry. Through a Template Analysis on semi-structured interviews with 14 game professionals, we reveal 12 overarching themes, structured into 49 sub-themes on professionals' perception, adoption and use of TTIG systems in games industry practice. Experiencing (yet another) change of roles and creative processes, our participants' reflections can inform discussions within the industry, be used by policymakers to inform urgently needed legislation, and support researchers in games, HCI and AI to support the sustainable, professional use of TTIG to benefit people and games as cultural artefacts.Comment: 32 pages (incl. appendix), 3 figures, 4 tables. Coding template (31 pages, 10 tables), study invitations (email, social media) and pre-study survey provided as supplementary (ancillary) material. Accepted with minor revisions at ACM CHI Play 202

    Utilizing gravity in movement-based games and play

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    This paper seeks to expand the understanding of gravity as a powerful but underexplored design resource for movement-based games and play. We examine how gravity has been utilized and manipulated in digital, physical, and mixed reality games and sports, considering five central and gravity-related facets of user experience: realism, affect, challenge, movement diversity, and sociality. For each facet, we suggest new directions for expanding the field of movement-based games and play, for example through novel combinations of physical and digital elements. Our primary contribution is a structured articulation of a novel point of view for designing games and interactions for the moving body. Additionally, we point out new research directions, and our conceptual framework can be used as a design tool. We demonstrate this in 1) creating and evaluating a novel gravity-based game mechanic, and 2) analyzing an existing movement-based game and suggesting future improvements

    Gender, Age, and Technology Education Influence the Adoption and Appropriation of LLMs

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    Large Language Models (LLMs) such as ChatGPT have become increasingly integrated into critical activities of daily life, raising concerns about equitable access and utilization across diverse demographics. This study investigates the usage of LLMs among 1,500 representative US citizens. Remarkably, 42% of participants reported utilizing an LLM. Our findings reveal a gender gap in LLM technology adoption (more male users than female users) with complex interaction patterns regarding age. Technology-related education eliminates the gender gap in our sample. Moreover, expert users are more likely than novices to list professional tasks as typical application scenarios, suggesting discrepancies in effective usage at the workplace. These results underscore the importance of providing education in artificial intelligence in our technology-driven society to promote equitable access to and benefits from LLMs. We urge for both international replication beyond the US and longitudinal observation of adoption

    Learning Task-Agnostic Action Spaces for Movement Optimization

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    We propose a novel method for exploring the dynamics of physically based animated characters, and learning a task-agnostic action space that makes movement optimization easier. Like several previous papers, we parameterize actions as target states, and learn a short-horizon goal-conditioned low-level control policy that drives the agent's state towards the targets. Our novel contribution is that with our exploration data, we are able to learn the low-level policy in a generic manner and without any reference movement data. Trained once for each agent or simulation environment, the policy improves the efficiency of optimizing both trajectories and high-level policies across multiple tasks and optimization algorithms. We also contribute novel visualizations that show how using target states as actions makes optimized trajectories more robust to disturbances; this manifests as wider optima that are easy to find. Due to its simplicity and generality, our proposed approach should provide a building block that can improve a large variety of movement optimization methods and applications.Comment: Accepted as a regular paper by IEEE Transactions on Visualization and Computer Graphics (TVCG) in July 202

    Voluntary pupil size change as control in eyes only interaction

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    We investigate consciously controlled pupil size as an input modality. Pupil size is affected by various processes, e.g., physical activation, strong emotional experiences and cognitive effort. Our hypothesis is that given continuous feedback, users can learn to control pupil size via physical and psychological self-regulation. We test it by measuring the magnitude of self evoked pupil size changes following seven different instructions, while providing real time graphical feedback on pupil size. Results show that some types of voluntary effort affect pupil size on a statistically significant level. A second controlled experiment confirms that subjects can produce pupil dilation and constriction on demand during paced tasks. Applications and limitations to using voluntary pupil size manipulation as an input modality are discussed. ACM Classification Keyword

    Metropolipolitiikan kehittÀmistarpeet

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    Työ on keskittynyt erityisesti metropolipolitiikkaan toimintatapana. Selvitystyön tavoitteena on metropolipolitiikan vaikuttavuuden parantaminen. TyössÀ on selvitetty muun muassa valtion ja seudun kuntien kumppanuuspohjaisen toimintatavan hyötyjÀ, vaikuttavimpia metropolipolitiikan vÀlineitÀ sekÀ metropolipolitiikan organisointitapaa. Selvityksen mukaan metropolipolitiikka on myötÀvaikuttanut Helsingin seudun kehitykseen koko Suomen hyvÀksi, ja sitÀ tarvitaan myös jatkossa. Tulevalla hallituskaudella tarvitaan kuitenkin aiempaa tarkemmin mÀÀriteltyjÀ tavoitteita, rajatumpia valintoja, sitovampia sopimuksia, tÀsmÀllisempiÀ vÀlineitÀ sekÀ tehokkaampaa organisoitumista. Selvityksen mukaan metropolipolitiikka on sijaiskÀrsinyt suurista rakenteellisista uudistusprosesseista, eivÀtkÀ toimijat ole olleet riittÀvÀn sitoutuneita yhteisten tavoitteiden toteuttamiseen. Onnistumisina selvitys nostaa esille erityisesti MAL-yhteensovittamisen ja pitkÀaikaisasunnottomuuden vÀhentÀmisohjelman. Selvityksen mukaan sisÀllöllisesti ei ole tarvetta tehdÀ radikaaleja muutoksia, mutta metropolipolitiikan ytimeksi kannattaisi asettaa kaksi asiaa: MAL-kysymykset sekÀ kasvu. Kasvuun liittyy olennaisesti kansainvÀlistyminen. Selvitys korostaa riittÀvÀn johtajuuden ja linjaamiskyvyn merkitystÀ metropolialueen keskeisissÀ kehittÀmiskysymyksissÀ, ja ehdottaa metropolipolitiikalle jatkossa tiiviimpÀÀ organisatorista ydintÀ, jossa on mukana korkein virkamies- ja poliittinen johto. Selvityksen on laatinut tammi-maaliskuussa 2015 MDI Public Oy Janne Antikaisen johdolla. Työ perustuu kirjalliseen aineistoon ja metropolipolitiikan neuvottelukunnan ja sihteeristön jÀsenten sekÀ asiantuntijoiden haastatteluihin
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