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Automatic Analysis of Players Behavior in Real Dyadic Chess Situations

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The present paper brings together solutions for full-automatic analysis of chess moves and eye tracking data for real dyadic chess games. We combine an electronic chessboard with marker detection in order to automatically protocol relevant and situation-related chess moves and visual attention patterns on pieces and squares. Very first results from initial evaluation studies indicate that the presented solution allows for a reliable automatic offline analysis of the underlying strategic and attentional processes of chess behaviour in real game situations without any need for an error prone and time consuming manual data annotation. The proposed solution allows to run chess studies in shorter time and to analyse the differences between chess experts and novices with respect to visual attention and strategies in more detail. Finally, gained insights can be used to develop interactive and intuitive electronic chess assistant systems to analyse the weaknesses of both experts and novices and to recommend optimal moves in given chess situations, as well as to enhance players' expertise with individualized training methods and explanations.
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hal-01617691 , version 1 (16-10-2017)


  • HAL Id : hal-01617691 , version 1


Thomas Küchelmann, Paola Carolina Torche, Manjunath Prasad, Kai Essig, Thomas Schack. Automatic Analysis of Players Behavior in Real Dyadic Chess Situations. 1st Workshop on “Behavior, Emotion and Representation: Building Blocks of Interaction”, Oct 2017, Bielefeld, Germany. ⟨hal-01617691⟩


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