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.
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Boccignone, G., Caggiano, V., Di Fiore, G., Marcelli, A., Napoletano, P. (2005). A Bayesian Approach to Situated Vision. In: De Gregorio, M., Di Maio, V., Frucci, M., Musio, C. (eds) Brain, Vision, and Artificial Intelligence. BVAI 2005. Lecture Notes in Computer Science, vol 3704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11565123_35
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DOI: https://doi.org/10.1007/11565123_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29282-1
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