The perception of objects in our visual world is influenced by not only their low-level visual features such as shape and color, but also their high-level features such as meaning and semantic relations among them. While it has been shown that low-level features in real-world scenes guide eye movements during scene inspection and search, the influence of semantic similarity among scene objects on eye movements in such situations has not been investigated. Here we study guidance of eye movements by semantic similarity among objects during real-world scene inspection and search. By selecting scenes from the LabelMe object-annotated image database and applying Latent Semantic Analysis (LSA) to the object labels, we generated semantic saliency maps of real-world scenes based on the semantic similarity of scene objects to the currently fixated object or the search target. An ROC analysis of these maps as predictors of subjects’ gaze transitions between objects during scene inspection revealed a preference for transitions to objects that were semantically similar to the currently inspected one. Furthermore, during the course of a scene search, subjects’ eye movements were progressively guided toward objects that were semantically similar to the search target. These findings demonstrate substantial semantic guidance of eye movements in real-world scenes and show its importance for understanding real-world attentional control.

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This work introduces a wearable system to provide situational awareness for blind and visually impaired people. The system includes a camera, an embedded computer and a haptic device to provide feedback when an obstacle is detected. The system uses techniques from computer vision and motion planning to (1) identify walkable space; (2) plan step-by-step a safe motion trajectory in the space, and (3) recognize and locate certain types of objects, for example the location of an empty chair. These descriptions are communicated to the person wearing the device through vibrations. We present results from user studies with low- and high-level tasks, including walking through a maze without collisions, locating a chair, and walking through a crowded environment while avoiding peopl

Latent semantic analysis (LSA) and transitional probability (TP), two computational methods used to reflect lexical semantic representation from large text corpora, were employed to examine the effects of word predictability on Chinese reading. Participants' eye movements were monitored, and the influence of word complexity (number of strokes), word frequency, and word predictability on different eye movement measures (first-fixation duration, gaze duration, and total time) were examined. We found influences of TP on first-fixation duration and gaze duration and of LSA on total time. The results suggest that TP reflects an early stage of lexical processing while LSA reflects a later stage.

When we look at real-world scenes, attention seems disproportionately attracted by texts that are embedded in these scenes, for instance, on signs or billboards. The present study was aimed at verifying the existence of this bias and investigating its underlying factors. For this purpose, data from a previous experiment were reanalyzed and four new experiments measuring eye movements during the viewing of real-world scenes were conducted. By pairing text objects with matching control objects and regions, the following main results were obtained: (a) Greater fixation probability and shorter minimum fixation distance of texts confirmed the higher attractiveness of texts; (b) the locations where texts are typically placed contribute partially to this effect; (c) specific visual features of texts, rather than typically salient features (e.g., color, orientation, and contrast), are the main attractors of attention; (d) the meaningfulness of texts does not add to their attentional capture; and (e) the attraction of attention depends to some extent on the observer's familiarity with the writing system and language of a given text.

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A previous study (Vision Research 51 (2011) 1192-1205) found evidence for semantic guidance of visual attention during the inspection of real-world scenes, i.e., an influence of semantic relationships among scene objects on overt shifts of attention. In particular, the results revealed an observer bias toward gaze transitions between semantically similar objects. However, this effect is not necessarily indicative of semantic processing of individual objects but may be mediated by knowledge of the scene gist, which does not require object recognition, or by known spatial dependency among objects. To examine the mechanisms underlying semantic guidance, in the present study, participants were asked to view a series of displays with the scene gist excluded and spatial dependency varied. Our results show that spatial dependency among objects seems to be sufficient to induce semantic guidance. Scene gist, on the other hand, does not seem to affect how observers use semantic information to guide attention while viewing natural scenes. Extracting semantic information mainly based on spatial dependency may be an efficient strategy of the visual system that only adds little cognitive load to the viewing task.

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