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< Back On the Behavioural Profiling of Gamblers Using Cryptocurrency Transaction Data Link Author(s) OJ Scholten Abstract More info TBA Link

< Back A comparison of the effects of haptic and visual feedback on presence in virtual reality Link Author(s) JK Gibbs, M Gillies, X Pan Abstract More info TBA Link

< Back User-centred collecting for emerging formats Link Author(s) F Smith Nicholls, GC Rossi, I Cooke, L Clark, T Pyke Abstract More info TBA Link

< Back Incremental game mechanics applied to text annotation Link Author(s) C Madge, R Bartle, J Chamberlain, U Kruschwitz, M Poesio Abstract More info TBA Link

< Back Expressivity of Parameterized and Data-driven Representations in Quality Diversity Search Link Author(s) A Hagg, S Berns, A Asteroth, S Colton, T Bäck Abstract More info TBA Link

< 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 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:

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

< 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

< 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

< 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

< 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