Bayesian theory of visual search

A bayesian optimal foraging model of human visual search.

Real-world visual searches often contain a variable and unknown number of targets. Such searches present difficult metacognitive challenges, as searchers must decide when to stop looking for additional targets, which results in high miss rates in multiple-target searches. In the study reported here, we quantified human strategies in multiple-target search via an ecological optimal foraging mode...

A Bayesian model for efficient visual search and recognition

Humans employ interacting bottom-up and top-down processes to significantly speed up search and recognition of particular targets. We describe a new model of attention guidance for efficient and scalable first-stage search and recognition with many objects (117,174 images of 1147 objects were tested, and 40 satellite images). Performance for recognition is on par or better than SIFT and HMAX, w...

What and where: a Bayesian inference theory of visual attention

In the theoretical framework described in this thesis, attention is part of the inference process that solves the visual recognition problem of what is where. The theory proposes a computational role for attention and leads to a model that predicts some of its main properties at the level of psychophysics and physiology. In our approach, the main goal of the visual system is to infer the identi...

Bayesian Inference in Models Based on Equilibrium Search Theory¤

The equilibrium search model represents a substantial advance over previous models of job search, but its empirical performance fails in some crucial ways. Hence, °exible extensions are called for. In this paper, we consider three such extensions in areas where Bayesian methods can be used to great advantage. These are: i) A speci ̄cation were Bayesian priors are used to center a model over the ...

A Detection by Compression Theory of "Visual Search"