Guided search: an alternative to the feature integration model for visual search

Subjects searched sets of items for targets defined by conjunctions of color and form, color and orientation, or color and size. Set size was varied and reaction times (RT) were measured. For many unpracticed subjects, the slopes of the resulting RT X Set Size functions are too shallow to be consistent with Treisman's feature integration model, which proposes serial, self-terminating search for conjunctions. Searches for triple conjunctions (Color X Size X Form) are easier than searches for standard conjunctions and can be independent of set size. A guided search model similar to Hoffman's (1979) two-stage model can account for these data. In the model, parallel processes use information about simple features to guide attention in the search for conjunctions. Triple conjunctions are found more efficiently than standard conjunctions because three parallel processes can guide attention more effectively than two.     

A two-stage model of visual search

A two-stage visual search model is described. Four experiments show that in a VM paradigm sequential presentation of the display leads to increases in accuracy and decreases in latency. Slower presentation rates allow for faster transfer of the target from iconic to short-term memory. When target and background items are dissimilar, transfer to short-term memory need not take place and decisions can be made on the basis of the Stage 1 analysis. These results are taken as confirming evidence for the proposed model.     

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 model and investigated whether searchers adapt their strategies to complex target-distribution statistics. Separate groups of individuals searched displays with the number of targets per trial sampled from different geometric distributions but with the same overall target prevalence. As predicted by optimal foraging theory, results showed that individuals searched longer when they expected more targets to be present and adjusted their expectations on-line during each search by taking into account the higher-order, across-trial target distributions. However, compared with modeled ideal observers, participants systematically responded as if the target distribution were more uniform than it was, which suggests that training could improve multiple-target search performance.     

A formal version of the Guided Search (GS2) model

Guided Search 2 (GS2) is currently one of the most detailed models of visual search and has been used to predict search times for different stimulus conditions by means of detailed computer simulations. The present article goes a step further and presents formulas that allow for the calculation of the search times and their variances. Moreover, these formulas can be applied to fit GS2 to data. An example is provided in which GS2 is fitted to search functions representing search asymmetries.     

A formal version of the Guided Search (GS2) model

Guided Search 2 (GS2) is currently one of the most detailed models of visual search and has been used to predict search times for different stimulus conditions by means of detailed computer simulations. The present article goes a step further and presents formulas that allow for the calculation of the search times and their variances. Moreover, these formulas can be applied to fit GS2 to data. An example is provided in which GS2 is fitted to search functions representing search asymmetries.     

A two-stage detection model applied to skilled visual search by radiologists

Harvard Medical School and Peter Bent Brigham Hospital, Boston, Massachusetts 02115 The model treats the detection of targets in a visual search task as a concatenation of two serial detection stages. Preattentive visual mechanisms in the initial stage function as a filter, selecting specific features of a visual pattern for the observer’s explicit attention and final cognitive evaluation. The model uses bivariate normal distributions to represent the decision variables for the two serial stages, assuming different parameters for the target and nontarget features in a test set. The model is applied to the detection performance of radiologists interpreting chest x-rays under various conditions of search. It accounts for the substantial improvement in radiologists’ ability to distinguish between target and nontarget test features when they had to search the x-ray images, compared to their performance without visual search. A change in the ROC curve between two different search tasks could be interpreted as a shift in the selection cutoff used by the preattentive filter.     

Eye movements in active visual search: A computable phenomenological model

We present a computational model and corresponding computer simulations that mimic phenomenologically the eye movement trajectories observed in a conjunctive visual search task. The element of randomness is captured in the model through a Monte Carlo selection of a particular eye movement based on its probability, which depends on three factors, adjusted to match to the observed saccade amplitude distribution, forward bias in consecutive saccades, and return rates. Memory is assumed to operate through tagging of objects already recognized as nontargets, which, in turn, requires their processing within the attentional area of conspicuity (AC). That AC is adjusted so that computer simulations optimally reproduce the distribution of the number of saccades, the failure rate for capturing the target, and the return rate to previously inspected locations. For their viability, computer simulations critically depend on memory’s being long-ranged. In turn, the simulations confirm the formation of circulating or spiraling patterns in the observed eye trajectories. We also relate consistently the average number of saccades per trial to the saccade amplitude distribution by modeling analytically the combined roles of the AC in attention and memory. The full Supplemental Appendix A for this article may be downloaded from http:// app.psychonomic-journals.org/content/supplemental.     

Guided search through memory

In “hybrid” search, observers search a visual display for any of several targets held in memory. It is known that the contents of the memory set can guide visual search (e.g., if the memorized targets are all animals, visual attention can be guided away from signs). It is not known if the visual display can guide memory search (e.g., if the memory set is composed of signs and animals, can a visual display of signs restrict memory search to just the signs?). In three hybrid search experiments, participants memorized sets of items that belonged to either one or several categories. Participants were then presented with visual displays containing multiple items, also drawn from one or several categories. Participants were asked to determine if any of the items from their current memory set were present in the visual display. We replicate the finding that visual search can be guided by the contents of memory. We find weaker, novel evidence that memory search can be guided by the contents of the visual display.     

A diffusion model of early visual search: Theoretical analysis and experimental results

Summary Meinecke (1989, Exp. 1, cond. HO) showed that the detectability of a visual target embedded in a linear noise array decreases with increasing retinal eccentricity, while the reaction time (RT) of the hits increases. One of the most interesting features of her results was that the RT of the correct rejections is consistently larger than the RT for signals presented near the fovea. This finding suggests that initially visual attention is concentrated near the fixation point and then diffuses across the stimulus array to perform a serial, exhaustive search. We present a diffusion model of early visual-search processes that quantitatively describes this evolution of attention in time and space; in contrast to most previous conceptions, it is based on a genuine relation between the spatial and temporal dimensions of the search processes performed. The model predicts quantitatively both detection performance and RT. We conducted an experiment similar to that of Meinecke (1989), but with an additional variation of the presentation time. All the main features of the 189 predictions could be explained by the model. The interpretation of the four model's parameters is discussed in some detail and compared with previous estimates of the microscopic search speed derived from alternative models. Finally, we consider some possible modifications related to results of Kehrer (1987, 1989), and some generalizations to multi target detection and two-dimensional stimulus arrays.     

Guided search for triple conjunctions

A key tenet of feature integration theory and of related theories such as guided search (GS) is that the binding of basic features requires attention. This would seem to predict that conjunctions of features of objects that have not been attended should not influence search. However, Found (1998) reported that an irrelevant feature (size) improved the efficiency of search for a Color × Orientation conjunction if it was correlated with the other two features across the display, as compared to the case in which size was not correlated with color and orientation features. We examined this issue with somewhat different stimuli. We used triple conjunctions of color, orientation, and shape (e.g., search for a red, vertical, oval-shaped item). This allowed us to manipulate the number of features that each distractor shared with the target (sharing) and it allowed us to vary the total number of distractor types (and, thus, the number of groups of identical items: grouping). We found that these triple conjunction searches were generally very efficient—producing very shallow Reaction Time × Set Size slopes, consistent with strong guidance by basic features. Nevertheless, both of the variables, sharing and grouping, modulated performance. These influences were not predicted by previous accounts of GS; however, both can be accommodated in a GS framework. Alternatively, it is possible, though not necessary, to see these effects as evidence for “preattentive binding” of conjunctions.     

A developmental study of visual search behavior

Children in second, fourth and sixth grades and college sophomores were compared on a visual search and scanning task under three experimental condilions. In Condition I, a single target letter was sought in a list of letters of low visual confusability. In Condition II, two target letters were sought but only one appeared in a given list. In Condition III, a single target letter was sought in a list of letters of high confusability. Search time decreased with age in all three tasks. Searching for two targets was no harder than searching for one. A highly confusable visual context increased search time at all age levels.     

A developmental study of visual search behavior

Children in second, fourth and sixth grades and college sophomores were compared on a visual search and scanning task under three experimental conditions. In Condition I, a single target letter was sought in a list of letters of low visual confusability. In Condition II, two target letters were sought but only one appeared in a given list. In Condition III, a single target letter was sought in a list of letters of high confusability. Search time decreased with age in all three tasks. Searching for two targets was no harder than searching for one. A highly confusable visual context increased search time at all age levels.     

A taxonomy of errors in multiple-target visual search

Multiple-target visual searches are especially error prone; once one target is found, additional targets are likely to be missed. This phenomenon, often called satisfaction of search (which we refer to here as subsequent search misses; SSMs), is well known in radiology, despite no existing consensus about the underlying cause(s). Taking a cognitive laboratory approach, we propose that there are multiple causes of SSMs and present a taxonomy of SSMs based on searchers' eye movements during a multiple-target search task, including both previously identified and novel sources of SSMs. The types and distributions of SSMs revealed effects of working memory load, search strategy, and additional causal factors, suggesting that there is no single cause of SSMs. A multifaceted approach is likely needed to understand the psychological causes of SSMs and then to mitigate them in applied settings such as radiology and baggage screening.     

Guided Search: The Effects of Learning

The previous report (Efron & Yund, 1996) offered an interpretation of the results of a number of search experiments within the theoretical context of the guided search model of Cave and Wolfe (1990) and Wolfe (1994). The present report extends this interpretation to the effects of extended practice when subjects search for a target defined by its orientation in the presence of a number of heterogeneous distractor items having differing orientations. Three experiments are described: The first revealed that over the course of 21 experimental sessions extending for a period of 6 weeks there were marked decreases in the magnitude of the reaction time gradient (RTG) and the right visual field superiority observed in the previous experiments. This learning persisted for more than 3 years. The second experiment revealed an interference in the capacity to learn to detect a target of one orientation when subjects had previously learned to detect a target of a different orientation at the same locations. The third experiment revealed that the learning was restricted to the area of the visual field where the target had been presented and that subjects could learn to detect two different targets concurrently. The results of these experiments indicate that the learning is orientation-specific and location-specific and is consistent with a localized increase in the selectivity of the top-down selection mechanism of the guided search model.     

In search of psychoticism: Some conclusions revised

Two reports of a substantial relationship between Psychoticism, as measured by the E.P.Q. P-scale, and the trait of Impulsiveness prompted a reanalysis of data, part of which had already formed the basis for the conclusion that individual differences in measured Psychoticism could best be accounted for in terms of the trait of Conformity. The inclusion of Impulsiveness as a variable in the reference set leads to the conclusion that most of the variance of Psychoticism can indeed be accounted for in terms of Impulsiveness, although Conformity still makes a non-trivial contribution.     

A conjunctive feature similarity effect for visual search

Traditional models of visual search assume interitem similarity effects arise from within each feature dimension independently of other dimensions. In the present study, we examine whether distractor–distractor effects also depend on feature conjunctions (i.e., whether feature conjunctions form a separate “feature” dimension that influences interitem similarity). Spatial frequency and orientation feature dimensions were used to generate distractors. In the bound condition, the number of distractors sharing the same conjunction of features was higher than that in the unbound condition, but the sharing of features within frequency and orientation dimensions was the same across conditions. The results showed that the target was found more efficiently in the bound than in the unbound condition, indicating that distractor–distractor similarity is also influenced by conjunctive representations.     

A conjunctive feature similarity effect for visual search

Traditional models of visual search assume interitem similarity effects arise from within each feature dimension independently of other dimensions. In the present study, we examine whether distractor-distractor effects also depend on feature conjunctions (i.e., whether feature conjunctions form a separate “feature” dimension that influences interitem similarity). Spatial frequency and orientation feature dimensions were used to generate distractors. In the bound condition, the number of distractors sharing the same conjunction of features was higher than that in the unbound condition, but the sharing of features within frequency and orientation dimensions was the same across conditions. The results showed that the target was found more efficiently in the bound than in the unbound condition, indicating that distractor-distractor similarity is also influenced by conjunctive representations.