id: 05321213
dt: a
an: 05321213
au: Thurau, Christian; Bauckhage, Christian; Sagerer, Gerhard
ti: Synthesizing movements for computer game characters.
so: Rasmussen, Carl Edward (ed.) et al., Pattern recognition. 26th DAGM
    symposium, Tübingen, Germany, August 30‒September 1, 2004.
    Proceedings. Berlin: Springer (ISBN 978-3-540-22945-2/pbk). Lecture
    Notes in Computer Science 3175, 179-186 (2004).
py: 2004
pu: Berlin: Springer
la: EN
cc: 
ut: 
ci: 
li: doi:10.1007/b99676
ab: Summary: Recent findings in biological neuroscience suggest that the brain
    learns body movements as sequences of motor primitives. Simultaneously,
    this principle is gaining popularity in robotics, computer graphics and
    computer vision: movement primitives were successfully applied to
    robotic control tasks as well as to render or to recognize human
    behavior. In this paper, we demonstrate that movement primitives can
    also be applied to the problem of implementing lifelike computer game
    characters. We present an approach to behavior modeling and learning
    that integrates several pattern recognition and machine learning
    techniques: trained with data from recorded multiplayer computer games,
    neural gas networks learn topological representation of virtual worlds;
    PCA is used to identify elementary movements the human players
    repeatedly executed during a match and complex behaviors are
    represented as probability functions mapping movement primitives to
    locations in the game environment. Experimental results underline that
    this framework produces game characters with humanlike skills.
rv: