Corrigendum: Where's Wally: the influence of visual salience on referring expression generation.

[This corrects the article DOI: 10.3389/fpsyg.2013.00329.].

Attentional Tunneling in Pilots During a Visual Tracking Task With a Head Mounted Display.

OBJECTIVE: We examined whether active head aiming with a Helmet Mounted Display (HMD) can draw the pilot's attention away from a primary flight task. Furthermore, we examined whether visual clutter increases this effect. BACKGROUND: Head up display symbology can result in attentional tunneling, and clutter makes it difficult to identify objects. METHOD: Eighteen military pilots had to simultaneously perform an attitude control task while flying in clouds and a head aiming task in a fixed-base flight simulator. The former consisted of manual compensation for roll disturbances of the aircraft, while the latter consisted of keeping a moving visual target inside a small or large head-referenced circle. A "no head aiming" condition served as a baseline. Furthermore, all conditions were performed with or without visual clutter. RESULTS: Head aiming led to deterioration of the attitude control task performance and an increase of the amount of roll-reversal errors (RREs). This was even the case when head aiming required minimal effort. Head aiming accuracy was significantly lower when the roll disturbances in the attitude control task were large compared to when they were small. Visual clutter had no effect on both tasks. CONCLUSION: We suggest that active head aiming of HMD symbology can cause attentional tunneling, as expressed by an increased number of RREs and less accuracy on a simultaneously performed attitude control task. APPLICATION: This study improves our understanding in the perceptual and cognitive effects of (military) HMDs, and has implications for operational use and possibly (re)design of HMDs.

Development of a quantitative measurement on visual clutter in see through display.

Objective: With the wide use of transmission displays to improve operation performance, the display information highlights clutter because of the contradiction between the massive amount of information and limited display area. Our study aimed to develop a quantitative measurement for declutter design and appraisal. Methods: Using the ergonomics research system of characters and symbols in a see-through cockpit display, we set the simulated flight task interface at four pixel scale levels by enlarging all the display elements in a certain ratio. Flight task videos of 12 clutter degrees were recorded using each flight interface matched with three flight scene complexity levels. A total of 60 pilots completed the visual search tasks in the flight task video while the eye tracker was used to record the view path in real time. Visual search performance was analyzed to study the effect of various clutter factors and levels on pilots' performance in visual search tasks, and acquire quantitative clutter measure parameters. Results: GLM univariate test revealed that there were significant differences among the fixation time in areas of interest (AOI), total Fixation point number, total fixation time at four pixel scale levels, and three flight scene complexity levels (P < 0.05). Visual search performance declined after the cutoff point, while the clutter degree increased. According to the visual search performance data, the recommend feature congestion upper pixel number limit in a 600*800 display was 18,576, and the pixel ratio was 3.87%. Conclusion: A quantitative measurement for declutter design and appraisal of cockpit displays was developed, which can be used to support see-through display design.

Using Virtual Reality to Systematically Examine Impacts of Noise and Visual Clutter on Message Elaboration and Cognitive Capacity.

This study used virtual reality to examine how environmental attributes interact with health communication to influence psychiatric help-seeking behavior, using the example of a subway station. We used a 2 × 2 factorial design crossing two noise conditions (high noise [75 dB] or low noise [30 dB]) and two visual clutter conditions (low clutter [a tidy trash can and orderly construction materials] or high clutter [scattered trash and construction materials]). We found that participants in the high (vs. low) visual clutter condition reported lower cognitive capacity levels, and there was a significant correlation between cognitive capacity and message elaboration. However, we found no effects of noise conditions. Serving as a proof-of-concept study to investigate the contexts in which environmental stressors may influence information processing, this study contributes to the field of health communication environmental design research. Clinical Trial Registration: https://osf.io/rsa48.

Background complexity can mitigate poor camouflage.

Avoiding detection through camouflage is often key to survival. However, an animal's appearance is not the only factor affecting conspicuousness: background complexity also alters detectability. This has been experimentally demonstrated for both artificially patterned backgrounds in the laboratory and natural backgrounds in the wild, but only for targets that already match the background well. Do habitats of high visual complexity provide concealment to even relatively poorly camouflaged animals? Using artificial prey which differed in their degrees of background matching to tree bark, we were able to determine their survival, under bird predation, with respect to the natural complexity of the background. The latter was quantified using low-level vision metrics of feature congestion (or 'visual clutter') adapted for bird vision. Higher background orientation clutter (edges with varying orientation) reduced the detectability of all but the poorest background-matching camouflaged treatments; higher background luminance clutter (varying achromatic lightness) reduced average mortality for all treatments. Our results suggest that poorer camouflage can be mitigated by more complex backgrounds, with implications for both camouflage evolution and habitat preferences.

Temporal scatterplots.

Visualizing high-dimensional data on a 2D canvas is generally challenging. It becomes significantly more difficult when multiple time-steps are to be presented, as the visual clutter quickly increases. Moreover, the challenge to perceive the significant temporal evolution is even greater. In this paper, we present a method to plot temporal high-dimensional data in a static scatterplot; it uses the established PCA technique to project data from multiple time-steps. The key idea is to extend each individual displacement prior to applying PCA, so as to skew the projection process, and to set a projection plane that balances the directions of temporal change and spatial variance. We present numerous examples and various visual cues to highlight the data trajectories, and demonstrate the effectiveness of the method for visualizing temporal data.

Pedestrian distraction: The effects of road environment complexity and age on pedestrian's visual attention and crossing behavior.

INTRODUCTION: Little is known about how characteristics of the environment affect pedestrians' road crossing behavior. METHOD: In this work, the effect of typical urban visual clutter created by objects and elements in the road proximity (e.g., billboards) on adults and children (aged 9-13) road crossing behavior was examined in a controlled laboratory environment, utilizing virtual reality scenarios projected on a large dome screen. RESULTS: Divided into three levels of visual load, results showed that high visual load affected children's and adults' road crossing behavior and visual attention. The main effect on participants' crossing decisions was seen in missed crossing opportunities. Children and adults missed more opportunities to cross the road when exposed to more cluttered road environments. An interaction with age was found in the dispersion of the visual attention measure. Children, 9-10 and 11-13 years old, had a wider spread of gazes across the scene when the environment was highly loaded-an effect not seen with adults. However, unexpectedly, no other indication of the deterring effect was found in the current study. Still, according to the results, it is reasonable to assume that busier road environments can be more hazardous to adult and child pedestrians. Practical Applications: In that context, it is important to further investigate the possible distracting effect of causal objects in the road environment on pedestrians, and especially children. This knowledge can help to create better safety guideline for children and assist urban planners in creating safer urban environments.

Efficiency improvement by navigated safety inspection involving visual clutter based on the random search model.

Navigated inspection seeks to improve hazard identification (HI) accuracy. With a tight inspection schedule, HI also requires efficiency. However, lacking quantification of HI efficiency, navigated inspection strategies cannot be comprehensively assessed. This work aims to determine inspection efficiency in navigated safety inspection, controlling for HI accuracy. Based on a cognitive method of the random search model (RSM), an experiment was conducted to observe the HI efficiency in navigation, for a variety of visual clutter (VC) scenarios, while using eye-tracking devices to record the search process and analyze the search performance. The results show that the RSM is an appropriate instrument, and VC serves as a hazard classifier for navigation inspection in improving inspection efficiency. This suggests a new and effective solution for addressing the low accuracy and efficiency of manual inspection through navigated inspection involving VC and the RSM. It also provides insights into the inspectors' safety inspection ability.

Influence of visual clutter on the effect of navigated safety inspection: a case study on elevator installation.

Introduction. Navigated safety inspection based on task-specific checklists can increase the hazard detection rate, theoretically with interference from scene complexity. Visual clutter, a proxy of scene complexity, can theoretically impair visual search performance, but its impact on the effect of safety inspection performance remains to be explored for the optimization of navigated inspection. This research aims to explore whether the relationship between working memory and hazard detection rate is moderated by visual clutter. Methods. Based on a perceptive model of hazard detection, we: (a) developed a mathematical influence model for construction hazard detection; (b) designed an experiment to observe the performance of hazard detection rate with adjusted working memory under different levels of visual clutter, while using an eye-tracking device to observe participants' visual search processes; (c) utilized logistic regression to analyze the developed model under various visual clutter. Conclusion. The effect of a strengthened working memory on the detection rate through increased search efficiency is more apparent in high visual clutter. This study confirms the role of visual clutter in construction-navigated inspections, thus serving as a foundation for the optimization of inspection planning.

How Distractor Objects Trigger Referential Overspecification: Testing the Effects of Visual Clutter and Distractor Distance.

In two experiments, we investigate to what extent various visual saliency cues in realistic visual scenes cause speakers to overspecify their definite object descriptions with a redundant color attribute. The results of the first experiment demonstrate that speakers are more likely to redundantly mention color when visual clutter is present in a scene as compared to when this is not the case. In the second experiment, we found that distractor type and distractor color affect redundant color use: Speakers are most likely to overspecify if there is at least one distractor object present that has the same type, but a different color than the target referent. Reliable effects of distractor distance were not found. Taken together, our results suggest that certain visual saliency cues guide speakers in determining which objects in a visual scene are relevant distractors, and which not. We argue that this is problematic for algorithms that aim to generate human-like descriptions of objects (such as the Incremental Algorithm), since these generally select properties that help to distinguish a target from all objects that are present in a scene.

Clutter perception is invariant to image size.

Two experiments evaluated the effect of retinal image size on the proto-object model of visual clutter perception. Experiment 1 had 20 participants order 90 small images of random-category real-world scenes from least to most cluttered. Aggregating these individual rankings into a single median clutter ranking and comparing it to a previously reported clutter ranking of larger versions of the identical scenes yielded a Spearman's ρ=.953 (p<.001), suggesting that relative clutter perception is largely invariant to image size. We then applied the proto-object model of clutter perception to these smaller images and obtained a clutter estimate for each. Correlating these estimates with the median behavioral ranking yielded a Spearman's ρ=.852 (p<.001), which we showed in a comparative analysis to be better than six other methods of estimating clutter. Experiment 2 intermixed large and small versions of the Experiment 1 scenes and had participants (n=18) again rank them for clutter. We found that median clutter rankings of these size-intermixed images were essentially the same as the small and large median rankings from Experiment 1, suggesting size invariance in absolute clutter perception. Moreover, the proto-object model again successfully captured this result. We conclude that both relative and absolute clutter perception is invariant to retinal image size. We further speculate that clutter perception is mediated by proto-objects-a preattentive level of visual representation between features and objects-and that using the proto-object model we may be able to glimpse into this pre-attentive world.

Modeling visual clutter perception using proto-object segmentation.

We introduce the proto-object model of visual clutter perception. This unsupervised model segments an image into superpixels, then merges neighboring superpixels that share a common color cluster to obtain proto-objects-defined here as spatially extended regions of coherent features. Clutter is estimated by simply counting the number of proto-objects. We tested this model using 90 images of realistic scenes that were ranked by observers from least to most cluttered. Comparing this behaviorally obtained ranking to a ranking based on the model clutter estimates, we found a significant correlation between the two (Spearman's ρ = 0.814, p < 0.001). We also found that the proto-object model was highly robust to changes in its parameters and was generalizable to unseen images. We compared the proto-object model to six other models of clutter perception and demonstrated that it outperformed each, in some cases dramatically. Importantly, we also showed that the proto-object model was a better predictor of clutter perception than an actual count of the number of objects in the scenes, suggesting that the set size of a scene may be better described by proto-objects than objects. We conclude that the success of the proto-object model is due in part to its use of an intermediate level of visual representation-one between features and objects-and that this is evidence for the potential importance of a proto-object representation in many common visual percepts and tasks.

Where's Wally: the influence of visual salience on referring expression generation.

REFERRING EXPRESSION GENERATION (REG) PRESENTS THE CONVERSE PROBLEM TO VISUAL SEARCH: given a scene and a specified target, how does one generate a description which would allow somebody else to quickly and accurately locate the target?Previous work in psycholinguistics and natural language processing has failed to find an important and integrated role for vision in this task. That previous work, which relies largely on simple scenes, tends to treat vision as a pre-process for extracting feature categories that are relevant to disambiguation. However, the visual search literature suggests that some descriptions are better than others at enabling listeners to search efficiently within complex stimuli. This paper presents a study testing whether participants are sensitive to visual features that allow them to compose such "good" descriptions. Our results show that visual properties (salience, clutter, area, and distance) influence REG for targets embedded in images from the Where's Wally? books. Referring expressions for large targets are shorter than those for smaller targets, and expressions about targets in highly cluttered scenes use more words. We also find that participants are more likely to mention non-target landmarks that are large, salient, and in close proximity to the target. These findings identify a key role for visual salience in language production decisions and highlight the importance of scene complexity for REG.