“High-Level Saliency Prediction for Smart Game Balancing” by Koulieris, Drettakis, Cunningham and Mania
Conference:
Type(s):
Title:
- High-Level Saliency Prediction for Smart Game Balancing
Session/Category Title: Perception
Presenter(s)/Author(s):
Abstract:
The first automated high-level saliency predictor that incorporates the schema and singleton hypotheses into the differential-weighting model. The predictor estimates the probabilities of objects to be attended and facilitates game-prop placement. Game difficulty is adjusted, since topology affects object-search completion time.
References:
BARTLETT, F. C. 1932. Remembering: An experimental and social study. Cambridge: Cambridge University.
ECKSTEIN, M. P. 1998. The lower visual search efficiency for conjunctions is due to noise and not serial attentional processing. Psychological Science 9, 2, 111–118.
SWEETSER, P., AND WYETH, P. 2005. Gameflow: a model for evaluating player enjoyment in games. Computers in Entertainment (CIE) 3, 3, 3–3.
THEEUWES, J., AND GODIJN, R. 2002. Irrelevant singletons capture attention: Evidence from inhibition of return. Perception & Psychophysics 64, 5, 764–770.
