The platformer experience dataset

Kostas Karpouzis, Georgios N. Yannakakis, Noor Shaker, Stylianos Asteriadis

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review


Player modeling and estimation of player experience have become very active research fields within affective computing, human computer interaction, and game artificial intelligence in recent years. For advancing our knowledge and understanding on player experience this paper introduces the Platformer Experience Dataset (PED) - the first open-access game experience corpus - that contains multiple modalities of user data of Super Mario Bros players. The open-access database aims to be used for player experience capture through context-based (i.e. game content), behavioral and visual recordings of platform game players. In addition, the database contains demographical data of the players and self-reported annotations of experience in two forms: ratings and ranks. PED opens up the way to desktop and console games that use video from webcameras and visual sensors and offer possibilities for holistic player experience modeling approaches that can, in turn, yield richer game personalization.
Original languageEnglish
Title of host publication2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015
Number of pages7
ISBN (Print)9781479999538
Publication statusPublished - 2 Dec 2015
Event2015 International Conference on Affective Computing and Intelligent Interaction - Xi'an, China
Duration: 21 Sept 201524 Sept 2015


Conference2015 International Conference on Affective Computing and Intelligent Interaction
Abbreviated titleACII 2015
Internet address


  • facial expression
  • head pose
  • mutimodal data corpus
  • platform games
  • player behavior
  • player experience
  • visual analysis

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