Abstract
How visual attention is shared between objects moving in an observed scene is a key issue to situate vision in the world. In this note, we discuss how a computational model taking into account such issue, can be designed in a bayesian framework. To validate the model, experiments with eye-tracked human subjects are presented and discussed. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Boccignone, G., Caggiano, V., Fiore, G. D., Marcelli, A., & Napoletano, P. (2005). A bayesian approach to situated vision. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3704 LNCS, pp. 367–376). https://doi.org/10.1007/11565123_35
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