Evaluating human visual search performance by Monte Carlo methods and heuristic model
Giacomo Veneri, Elena Pretegiani, Pamela Federighi, Francesca Rosini, Antonio Federico, Alessandra Rufa · 2010
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.