Visual search for arbitrary objects in real scenes.

How efficient is visual search in real scenes? In searches for targets among arrays of randomly placed distractors, efficiency is often indexed by the slope of the reaction time (RT) × Set Size function. However, it may be impossible to define set size for real scenes. As an approximation, we hand-labeled 100 indoor scenes and used the number of labeled regions as a surrogate for set size. In Experiment 1, observers searched for named objects (a chair, bowl, etc.). With set size defined as the number of labeled regions, search was very efficient (~5 ms/item). When we controlled for a possible guessing strategy in Experiment 2, slopes increased somewhat (~15 ms/item), but they were much shallower than search for a random object among other distinctive objects outside of a scene setting (Exp. 3: ~40 ms/item). In Experiments 4-6, observers searched repeatedly through the same scene for different objects. Increased familiarity with scenes had modest effects on RTs, while repetition of target items had large effects (>500 ms). We propose that visual search in scenes is efficient because scene-specific forms of attentional guidance can eliminate most regions from the "functional set size" of items that could possibly be the target.

How many pixels make a memory? Picture memory for small pictures.

Torralba (Visual Neuroscience, 26, 123-131, 2009) showed that, if the resolution of images of scenes were reduced to the information present in very small "thumbnail images," those scenes could still be recognized. The objects in those degraded scenes could be identified, even though it would be impossible to identify them if they were removed from the scene context. Can tiny and/or degraded scenes be remembered, or are they like brief presentations, identified but not remembered. We report that memory for tiny and degraded scenes parallels the recognizability of those scenes. You can remember a scene to approximately the degree to which you can classify it. Interestingly, there is a striking asymmetry in memory when scenes are not the same size on their initial appearance and subsequent test. Memory for a large, full-resolution stimulus can be tested with a small, degraded stimulus. However, memory for a small stimulus is not retrieved when it is tested with a large stimulus.

Color channels, not color appearance or color categories, guide visual search for desaturated color targets.

In this article, we report that in visual search, desaturated reddish targets are much easier to find than other desaturated targets, even when perceptual differences between targets and distractors are carefully equated. Observers searched for desaturated targets among mixtures of white and saturated distractors. Reaction times were hundreds of milliseconds faster for the most effective (reddish) targets than for the least effective (purplish) targets. The advantage for desaturated reds did not reflect an advantage for the lexical category "pink," because reaction times did not follow named color categories. Many pink stimuli were not found quickly, and many quickly found stimuli were not labeled "pink." Other possible explanations (e.g., linear-separability effects) also failed. Instead, we propose that guidance of visual search for desaturated colors is based on a combination of low-level color-opponent signals that is different from the combinations that produce perceived color. We speculate that this guidance might reflect a specialization for human skin.

The speed of free will.

Do voluntary and task-driven shifts of attention have the same time course? In order to measure the time needed to voluntarily shift attention, we devised several novel visual search tasks that elicited multiple sequential attentional shifts. Participants could only respond correctly if they attended to the right place at the right time. In control conditions, search tasks were similar but participants were not required to shift attention in any order. Across five experiments, voluntary shifts of attention required 200-300 ms. Control conditions yielded estimates of 35-100 ms for task-driven shifts. We suggest that the slower speed of voluntary shifts reflects the "clock speed of free will". Wishing to attend to something takes more time than shifting attention in response to sensory input.