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  • Investigating the non-disruptive measurement of immersive player experience

    < Back Investigating the non-disruptive measurement of immersive player experience Link Author(s) MT Aung Abstract More info TBA Link

  • Novel video narrative from recorded content | iGGi PhD

    Novel video narrative from recorded content Theme Creative Computing Project proposed & supervised by Nick Pears To discuss whether this project could become your PhD proposal please email: nick.pears@york.ac.uk < Back Novel video narrative from recorded content Project proposal abstract: In order to stimulate interest and engagement in games, it is important to give players a wide variety of video content that can provide scenario variations each time they engage with the game. However, creating a large volume of diverse video content manually is expensive and time consuming. This project aims to generate novel video narratives from recorded content with minimal human intervention. This requires automatic visual scene understanding that generates auto tagging of scene content and scene actions, either on a frame-by-frame or short clip basis. As well as understanding frame content, action segmentation strategies will be developed and evaluated. This will enable construction of short novel video narratives - for example, from a manually-defined storyline. Deep learning tools and techniques will be employed throughout this project. Supervisor: Nick Pears Based at:

  • Spirit AI

    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. Spirit AI

  • The n-tuple bandit evolutionary algorithm for automatic game improvement

    < Back The n-tuple bandit evolutionary algorithm for automatic game improvement Link Author(s) K Kunanusont, RD Gaina, J Liu, D Perez-Liebana, SM Lucas Abstract More info TBA Link

  • Characteristics and motivations of players with disabilities in digital games

    < Back Characteristics and motivations of players with disabilities in digital games Link Author(s) J Beeston, C Power, P Cairns, M Barlet Abstract More info TBA Link

  • Busy doing nothing? What do players do in idle games?

    < Back Busy doing nothing? What do players do in idle games? Link Author(s) J Cutting, D Gundry, P Cairns Abstract More info TBA Link

  • Redundancy Resolution in Trimanual vs. Bimanual Tracking Tasks

    < Back Redundancy Resolution in Trimanual vs. Bimanual Tracking Tasks Link Author(s) A Sanmartín-Senent, N Peña-Perez, E Burdet, J Eden Abstract More info TBA Link

  • Visualising Generative Spaces Using Convolutional Neural Network Embeddings

    < Back Visualising Generative Spaces Using Convolutional Neural Network Embeddings Link Author(s) O Withington, L Tokarchuk Abstract More info TBA Link

  • Controlling co-incidental non-player characters

    < Back Controlling co-incidental non-player characters Link Author(s) J Walton-Rivers Abstract More info TBA Link

  • InteractML: Node Based Tool to Empower Artists and Dancers in using Interactive Machine Learning for Designing Movement Interaction

    < Back InteractML: Node Based Tool to Empower Artists and Dancers in using Interactive Machine Learning for Designing Movement Interaction Link Author(s) C Hilton, C Gonzalez Diaz, R Gibson, P Perry, R Fiebrink, M Zbyszynski, ... Abstract More info TBA Link

  • iGGi conference 2021 | iGGi PhD

    < Back iGGi conference 2021 Mark the date for our next IGGI Conference: 08 - 09 September 2021 PhD students discuss and showcase their research into new technologies and directions for games.Come along and find out about new ideas, meet future employees, and steer the direction of research in the world’s largest games PhD programme. Click for Tickets and more info here - coming soon Previous 8 Jul 2021 Next

  • League of Legends: A Study of Early Game Impact

    < Back League of Legends: A Study of Early Game Impact Link Author(s) R Gaina, C Nordmoen Abstract More info TBA Link

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The EPSRC Centre for Doctoral Training in Intelligent Games and Game Intelligence (iGGi) is a leading PhD research programme aimed at the Games and Creative Industries.

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