On the Hunt: Searching for Poorly Defined Camouflaged Targets

Hess, Alyssa; Wismer, Andrew; Bohil, Corey J.; Neider, Mark

doi:10.1371/journal.pone.0152502

Cited by 5 publications

(6 citation statements)

References 27 publications

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“…While lifeguard surveillance shares similarities with visual search in other domains, there are limitations when making comparisons. Real-world visual searches that are reported in the literature often focus on static images, which either have a target present throughout the search or no target object at all (Alexander & Zelinsky, 2012; Hess et al, 2016; Peelen & Kastner, 2014). In these traditional search tasks, participants are required to indicate if the target is present or absent, for example, detecting a dangerous item in an airport security scan (Biggs & Mitroff, 2014).…”

Section: Assessing Lifeguards’ Visual Search Skillsmentioning

confidence: 99%

Search for a distressed swimmer in a dynamic, real-world environment.

Laxton¹,

Guest²,

Howard³

et al. 2021

Journal of Experimental Psychology: Applied

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Visual search is increasingly being explored in dynamic, real-world environments. This includes swimming pools, where lifeguards have shown superior drowning detection in simulated environments. Here we explored if lifeguard superiority is observed in real-life scenes of a busy swimming pool. Experiment 1 required participants to identify real-life distressed swimmers in clips of busy pool activity via a touchscreen interface. Experiment 2 sought to replicate the first study, with the inclusion of eye-movement measures.Experiment 3 varied the methodology, using an occlusion method where clips were frozen and blurred shortly after target onset. The results demonstrated an experience effect, with lifeguards detecting distressed swimmers more often and faster than non-lifeguards. No clear differences were found in the eye-movements between groups; thus, we cannot conclude that the lifeguards' faster responses are due to better scanning strategies. The different methodological approaches revealed the occlusion method to have the larger effect size, supporting the growing evidence that occlusion may be a better test for dynamic target detection than traditional response-time tests. This research demonstrates that the clear lifeguard experience effect generalises to real-life pool environments with a large number of swimmers and real incidents. It could be used to inform lifeguard training tools and assessments.

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Section: Assessing Lifeguards’ Visual Search Skillsmentioning

confidence: 99%

Search for a distressed swimmer in a dynamic, real-world environment.

Laxton¹,

Guest²,

Howard³

et al. 2021

Journal of Experimental Psychology: Applied

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“…To help determine whether and to what extent the stimulus duration per se affected the accuracy of target localization, we examined the accuracy of localization for the stimulus duration of 50 ms. Note that a stimulus duration this brief allows for little in the way of eye movements (Ibbotson & Krekelberg, 2011 ; Kowler, 2011 ) [also see (Hess et al, 2016 )]. Nonetheless, subjects were able to localize the target in this case as well (Fig.…”

Section: Resultsmentioning

confidence: 99%

Expert camouflage-breakers can accurately localize search targets

et al. 2021

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Camouflage-breaking is a special case of visual search where an object of interest, or target, can be hard to distinguish from the background even when in plain view. We have previously shown that naive, non-professional subjects can be trained using a deep learning paradigm to accurately perform a camouflage-breaking task in which they report whether or not a given camouflage scene contains a target. But it remains unclear whether such expert subjects can actually detect the target in this task, or just vaguely sense that the two classes of images are somehow different, without being able to find the target per se. Here, we show that when subjects break camouflage, they can also localize the camouflaged target accurately, even though they had received no specific training in localizing the target. The localization was significantly accurate when the subjects viewed the scene as briefly as 50 ms, but more so when the subjects were able to freely view the scenes. The accuracy and precision of target localization by expert subjects in the camouflage-breaking task were statistically indistinguishable from the accuracy and precision of target localization by naive subjects during a conventional visual search where the target ‘pops out’, i.e., is readily visible to the untrained eye. Together, these results indicate that when expert camouflage-breakers detect a camouflaged target, they can also localize it accurately.

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“…The image manipulations used for the ODDS scenes were modeled after those used by Hess et al ( 2016 ), who studied search for camouflaged targets. “Camouflage-breaking” can be considered a special instance of visual search wherein observers must identify objects of interest that blend into the background (Branch et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

“…1 Criteria for selection included: (1) landscape orientation, (2) greater than or equal to 1920 × 1080 (width and height, respectively) resolution, and (3) the majority of the image must contain meaningful content (e.g., images with large open skies or blank walls were avoided because deforming flat surfaces results in targets that are nearly impossible to discriminate from the background). The original images were manipulated to contain an “oddity” target in the form of a ripple deformation in the scene (see Hess et al, 2016 , for a similar image manipulation method). Each scene was manipulated multiple (independent) times, creating 16 variants of the original, each with a target located in a different spatial position (for a total of 4576 edited images).…”

Section: The Oddity Detection In Diverse Scenes (Odds) Databasementioning

confidence: 99%

“…We suggest that creating a stimulus set that captures structural regularity, visual noise, and target ambiguity may be a first step toward developing laboratory paradigms that can reveal insights into the mechanisms of anomaly detection that characterize radiological scanning. To that end, we modified scenes of libraries/books, interior rooms, and forests to include subtle “ripple” deformations, similar to those used in research on camouflaged targets (Hess et al, 2016 ). Although ripple deformations embedded within scenes are not a perfect approximation for anomalies located in medical images, we suggest that they are more appropriate than standard template-defined targets in many standard search tasks.…”

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confidence: 99%

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The Oddity Detection in Diverse Scenes (ODDS) database: Validated real-world scenes for studying anomaly detection

Hout

Papesh²,

Masadeh³

et al. 2022

Behav Res

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Many applied screening tasks (e.g., medical image or baggage screening) involve challenging searches for which standard laboratory search is rarely equivalent. For example, whereas laboratory search frequently requires observers to look for precisely defined targets among isolated, non-overlapping images randomly arrayed on clean backgrounds, medical images present unspecified targets in noisy, yet spatially regular scenes. Those unspecified targets are typically oddities, elements that do not belong. To develop a closer laboratory analogue to this, we created a database of scenes containing subtle, ill-specified “oddity” targets. These scenes have similar perceptual densities and spatial regularities to those found in expert search tasks, and each includes 16 variants of the unedited scene wherein an oddity (a subtle deformation of the scene) is hidden. In Experiment 1, eight volunteers searched thousands of scene variants for an oddity. Regardless of their search accuracy, they were then shown the highlighted anomaly and rated its subtlety. Subtlety ratings reliably predicted search performance (accuracy and response times) and did so better than image statistics. In Experiment 2, we conducted a conceptual replication in which a larger group of naïve searchers scanned subsets of the scene variants. Prior subtlety ratings reliably predicted search outcomes. Whereas medical image targets are difficult for naïve searchers to detect, our database contains thousands of interior and exterior scenes that vary in difficulty, but are nevertheless searchable by novices. In this way, the stimuli will be useful for studying visual search as it typically occurs in expert domains: Ill-specified search for anomalies in noisy displays.

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On the Hunt: Searching for Poorly Defined Camouflaged Targets

Cited by 5 publications

References 27 publications

Search for a distressed swimmer in a dynamic, real-world environment.

Search for a distressed swimmer in a dynamic, real-world environment.

Expert camouflage-breakers can accurately localize search targets

The Oddity Detection in Diverse Scenes (ODDS) database: Validated real-world scenes for studying anomaly detection

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