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Realistic physical interaction of 3D point cloud objects Theme Design and Development Project proposed & supervised by Miles Hansard, Changjae Oh To discuss whether this project could become your PhD proposal please email: miles.hansard@qmul.ac.uk < Back ​ Realistic physical interaction of 3D point cloud objects Project proposal abstract: Point cloud data is becoming widely available, owing to commodity depth cameras and lidar systems. This creates many opportunities for creating 3D game assets, including environments and objects, from scanned real-world data. The realistic rendering of such data has been widely investigated (e.g. https://hal.inria.fr/hal-01017700/) , and can be performed efficiently. However, physical interactions between point clouds, meshes, and other representations are also critical, for gaming and VR applications. These interactions, which include collision, deformation, occlusion, and other effects, may require alternative representations (e.g. https://arxiv.org/abs/1912.12033) . This project will investigate geometric and machine learning approaches to these open problems, in typical game environments. Supervisor: Miles Hansard , Changjae Oh Based at:

< Back Echo Suite of Software (Showcase Brochure) Link ​ Author(s) Florian Oliver Block, Marian Ursu, Jonathan David Hook, Ben Kirman, Anders Drachen, Simon Peter Demediuk, Athanasios Kokkinakis, [...], Alan Pedrassoli Chitayat, ... Abstract ​ More info TBA ​ Link

< Back Quality Evolvability ES: Evolving Individuals With a Distribution of Well Performing and Diverse Offspring Link ​ Author(s) A Katona, DW Franks, JA Walker Abstract ​ More info TBA ​ Link

< Back Sketching and Layering Graffiti Primitives. Link ​ Author(s) D Berio, P Asente, J Echevarria, FF Leymarie Abstract ​ More info TBA ​ Link

< Back Evolving UCT alternatives for general video game playing Link ​ Author(s) I Bravi Abstract ​ More info TBA ​ Link

< Back Immersive Technology How might we advance the use and understanding of VR, XR, AR, and other immersive technologies in games? Project areas include: Generating 3D game assets from 2D images Using machine learning to enhance interaction with virtual characters in games << Previous Theme page Next Theme page >> iGGi >>> People <<< relevant to this Theme: Dr Guifen Chen Supervisor ​ Creative Computing, Design & Development, Immersive Technology, Player Research Read More Dr Cristina Dobre iGGi Alum ​ Game AI, Immersive Technology Read More Dr Ildar Farkhatdinov Supervisor ​ Design & Development, Game AI, Immersive Technology, Player Research Read More Dr Miles Hansard Supervisor ​ Game AI, Immersive Technology, Design & Development, Game Data Read More Karl Clarke iGGi PG Researcher Available for placement Design & Development, Immersive Technology, Player Research Read More Dr Abi Evans Supervisor ​ Design & Development, Immersive Technology, Player Research Read More Luke Farrar iGGi PG Researcher ​ Immersive Technology Read More Dr Patrik Huber Supervisor ​ Applied Games, Game Data, Immersive Technology, Player Research, Esports Read More Tania Dales iGGi PG Researcher Available for placement Game AI, Design & Development, Immersive Technology, Player Research Read More Dr Timea Farkas iGGi Alum ​ Player Research, Creative Computing, Immersive Technology Read More Dr Carlos Gonzalez Diaz iGGi Alum ​ Immersive Technology, Game AI, Design & Development, Creative Computing Read More Dr Yul HR Kang Supervisor ​ Game AI, Player Research, Creative Computing, Immersive Technology Read More Load More iGGi People working in this Theme iGGi >>> Publications <<< relevant to this Theme: The Sky's the Limit: Re-lightable Outdoor Scenes via a Sky-pixel Constrained Illumination Prior and Outside-In Visibility JAD Gardner, E Kashin, B Egger, WAP Smith arXiv preprint arXiv:2311.16937, 2023 Evgenii Kashin View Details Making Space for Social Time: Supporting Conversational Transitions Before, During, and After Video Meetings C Gonzalez Diaz, J Tang, A Sarkar, S Rintel 2022 Symposium on Human-Computer Interaction for Work, 1-11, 2022 Dr Carlos Gonzalez Diaz View Details InteractML: Making machine learning accessible for creative practitioners working with movement interaction in immersive media C Hilton, N Plant, C González Díaz, P Perry, R Gibson, B Martelli, ... Proceedings of the 27th ACM Symposium on Virtual Reality Software and …, 2021 Dr Carlos Gonzalez Diaz View Details Interactive Machine Learning for Embodied Interaction Design: A tool and methodology N Plant, C Hilton, M Gillies, R Fiebrink, P Perry, C González Díaz, ... Proceedings of the Fifteenth International Conference on Tangible, Embedded …, 2021 Dr Carlos Gonzalez Diaz View Details Bodystorming in SocialVR to Support Collaborative Embodied Ideation C Gonzalez Diaz, R Fiebrink, P Perry, R Gibson, B Martelli, S Deterding, ... CHI 2021 Workshop on SocialVR, 3, 2021 Dr Carlos Gonzalez Diaz View Details InteractML: Node Based Tool to Empower Artists and Dancers in using Interactive Machine Learning for Designing Movement Interaction C Hilton, C Gonzalez Diaz, R Gibson, P Perry, R Fiebrink, M Zbyszynski, ... Workshop "The UX of Interactive Machine Learning" at NordiCHI 2020 Dr Carlos Gonzalez Diaz View Details Load More iGGi Publications for this Theme Previous Next

< Back ​ Dr Charles Ringer University of York ​ iGGi Alum ​ ​ Charlie Ringer is a researcher interested in applied Machine Learning with a focus on the ways in which we can use Deep Learning to model various facets of video games streams (e.g. stream highlights, emotional moments, in-game events, various streamer behaviours etc.). As such, his work spans many Machine Learning fields, such as Computer Vision, Affect Computing, and Natural Language Processing. His research has three motivating factors. Firstly, the challenge of how to fuse multi-view stream data (e.g. audio, web-cam footage, game footage, chat) into a single model, especially when considering the challenges of ‘in-the-wild’ data. Secondly, the untapped and bountiful data source that livestreaming represents, especially regarding the way in which streamers play games and interact with their audience. Thirdly, the exciting and emerging field of self-supervised learning which has the potential to utilise this abundance of livestream data. Charlie initially worked in the video games industry working mainly on the Magic: The Gathering - Duels of the Planeswalkers series of games before studying a BSc in Computer Science at Goldsmiths, University of London. After his BSc he joined IGGI, firstly at Goldsmiths and then at York. He was recognised as a finalist for the Twitch Research Fellowship 2019 for his research on livestream data. ​ charles.ringer@york.ac.uk Email Mastodon https://www.charlieringer.com Other links Website https://www.linkedin.com/in/charlie-ringer/ LinkedIn https://www.twitter.com/charlieringer Twitter https://www.github.com/charlieringer Github ​ Featured Publication(s): Machine Learning with Applications From Theory to Behaviour: Towards a General Model of Engagement Modelling early user-game interactions for joint estimation of survival time and churn probability Time to die 2: Improved in-game death prediction in dota 2 Autohighlight: Highlight Detection in League of Legends Esports Broadcasts via Crowd-Sourced Data Multi-Modal Livestream Highlight Detection from Audio, Visual, and Language Data Twitchchat: A dataset for exploring livestream chat Multimodal joint emotion and game context recognition in league of legends livestreams Streaming Behaviour: Livestreaming as a Paradigm for Analysis of Emotional and Social Signals Deep unsupervised multi-view detection of video game stream highlights Streaming behaviour: Live streaming as a paradigm for multi-view analysis of emotional and social signals Rolling Horizon Co-evolution in Two-player General Video Game Playing Themes Esports Game AI Game Data - Previous Next

< Back ​ Dr Lorenzo Jamone Queen Mary University of London ​ Supervisor ​ ​ I am a Lecturer in Robotics and Director of the CRISP group (Cognitive Robotics and Intelligent Systems for the People) at the School of Electronic Engineering and Computer Science (EECS) of the Queen Mary University of London (QMUL). The CRISP group is part of ARQ (Advanced Robotics at Queen Mary). Since October 2018, I have been a Turing Fellow at The Alan Turing Institute. I am interested in understanding human (and animal) intelligence, by using computational techniques that include computer simulations and real robots. My research topics include: human creativity and creative problem solving, human perception, human-human non-verbal communication, object affordances, tool use, body schema, eye-hand coordination, dexterous manipulation and object exploration, human-robot interaction and collaboration, tactile and force sensing. I am interested in supervising students with an engineering, computer science or behavioural sciences background on the following topics: Creating computational models of human creativity Creating computational models of decisional agents ​ l.jamone@qmul.ac.uk Email Mastodon https://lorejam.wixsite.com/crisp Other links Website LinkedIn Twitter Github ​ ​ Themes Applied Games Creative Computing - Previous Next

< Back ​ Oliver Roughton University of York iGGi Administrator iGGi Admin ​ ​ Based in York alongside Tracy and Helen I act as a Point of contact for iGGi PGRs and provide administrative support in the implementation of iGGi procedures. iGGi PGRs are most likely to hear from me in relation to conference/kit funding and travel bookings for the taught modules and other iGGi events. As well as my admin work I am a part-time PhD student (not with iGGi) and spend much of my free time knitting. ​ oliver.roughton@york.ac.uk Email https://www.instagram.com/klaus.the.magnificent/ Mastodon Other links Website LinkedIn Twitter Github ​ ​ Themes Previous Next

< Back What makes icons appealing? The role of processing fluency in predicting icon appeal in different task contexts Link ​ Author(s) S McDougall, I Reppa, J Kulik, A Taylor Abstract ​ More info TBA ​ Link

Understanding ongoing mental states using video games: applications to mental health research. Theme Game Data Project proposed & supervised by Alex Wade To discuss whether this project could become your PhD proposal please email: alex.wade@york.ac.uk < Back ​ Understanding ongoing mental states using video games: applications to mental health research. Project proposal abstract: A player’s behaviour in a game is directly linked to their personality and gives detailed information on their decision making processes, showing how they approach risks, socialisation and problem solving. Analysing these behaviours may also provide information about mental health disorders and indicate how these change over time. Neuroimaging methods (EEG/MEG/fMRI) can be used to examine the neural responses and patterns of ongoing neuronal activity that occur while players are engaged in a game. By linking these data to modern theories of neural economics we can explore and potentially improve aspects of a player's decision making, such as: attention span, focus, risk taking and delayed reward. This PhD will use a combination of neuroscience and advanced data analysis methods to examine the link between video game play and the brain. We will use a combination of cutting-edge data analytic techniques applied to large, existing video game telemetry datasets and neuroimaging experiments designed to measure changes in ongoing mental states while people play simple video games. The PhD would suit a student with good data analytics skills and some experience in neuroscience. Supervisor: Alex Wade Based at:

iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: ​ Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! ​ There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. University of California, Irvine