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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. HandCircus

< Back Interactive generation of calligraphic trajectories from Gaussian mixtures Link Author(s) D Berio, FF Leymarie, S Calinon Abstract More info TBA Link

< Back Dissociating haptic feedback from physical assistance does not improve motor performance Link Author(s) E Ivanova, N Pena-Perez, J Eden, Y Yip, E Burdet Abstract More info TBA Link

< Back The State of the Art in Procedural Audio Link Author(s) D Menexopoulos, P Pestana, J Reiss Abstract More info TBA Link

< Back UCL+ Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound Link Author(s) J Goodman, A Vlachos, J Naradowsky Abstract More info TBA Link

< Back Archaeological Gameworld Affordances: A Grounded Theory of How Players Interpret Environmental Storytelling Link Author(s) F Smith Nicholls, M Cook Abstract More info TBA Link

< Back The Graph Cut Kernel for Ranked Data Link Author(s) M Conserva, MP Deisenroth, KSS Kumar 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:

< Back Do People Use Games to Compensate for Psychological Needs During Crises? A Mixed-Methods Study of Gaming During COVID-19 Lockdowns Link Author(s) N Ballou, S Deterding, I Iacovides, L Helsby 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 Automatic Generation of Text for Match Recaps using Esport Caster Commentaries Link Author(s) O Olarewaju, AV Kokkinakis, S Demediuk, J Roberstson, I Nölle, S Patra, D Slawson, AP Chitayat, A Coates, B Kirman, A Drachen, M Ursu, F Block, J Hook Abstract More info TBA Link

< Back Streaming Behaviour: Livestreaming as a Paradigm for Analysis of Emotional and Social Signals Link Author(s) C Ringer, MA Nicolaou Abstract More info TBA Link