Visual search is an everyday activity that enables humans to explore the real world. Given the visual input, during a visual search, it's required to select some aspects of the input in order to move to the next location. Exploration is guided by two factors: saliency of image (bottom-up) and endogenous mechanism (top-down). These two mechanisms interact to perform an efficient visual search. We developed a stochastic model, the "break away from fixations" (BAF), to emulate the visual search on a high cognitively demanding task such as a trail making test (TMT). The paper reports a case study providing evidence that human exploration performs an efficient visual search based also on an internal model of regions already explored. © 2010 IEEE.

Veneri, G., Pretegiani, E., Federighi, P., Rosini, F., Federico, A., Rufa, A. (2010). Evaluating human visual search performance by Monte Carlo methods and heuristic model. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1-4 [10.1109/ITAB.2010.5687697].

Evaluating human visual search performance by Monte Carlo methods and heuristic model

Pretegiani, Elena;Federighi, Pamela;Rosini, Francesca;Federico, Antonio;Rufa, Alessandra
2010-01-01

Abstract

Visual search is an everyday activity that enables humans to explore the real world. Given the visual input, during a visual search, it's required to select some aspects of the input in order to move to the next location. Exploration is guided by two factors: saliency of image (bottom-up) and endogenous mechanism (top-down). These two mechanisms interact to perform an efficient visual search. We developed a stochastic model, the "break away from fixations" (BAF), to emulate the visual search on a high cognitively demanding task such as a trail making test (TMT). The paper reports a case study providing evidence that human exploration performs an efficient visual search based also on an internal model of regions already explored. © 2010 IEEE.
Veneri, G., Pretegiani, E., Federighi, P., Rosini, F., Federico, A., Rufa, A. (2010). Evaluating human visual search performance by Monte Carlo methods and heuristic model. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1-4 [10.1109/ITAB.2010.5687697].
File in questo prodotto:
File Dimensione Formato  
Veneri G Evaluating Visual Search performance by Monte Carlo methods and Heuristic IEEEX 2010.pdf

non disponibili

Tipologia: PDF editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 1.18 MB
Formato Adobe PDF
1.18 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1024750