Seeing structure: Shape skeletons modulate perceived similarity

An intrinsic part of seeing objects is seeing how similar or different they are relative to one another. This experience requires that objects be mentally represented in a common format over which such comparisons can be carried out. What is that representational format? Objects could be compared in terms of their superficial features (e.g., degree of pixel-by-pixel overlap), but a more intriguing possibility is that they are compared on the basis of a deeper structure. One especially promising candidate that has enjoyed success in the computer vision literature is the shape skeleton—a geometric transformation that represents objects according to their inferred underlying organization. Despite several hints that shape skeletons are computed in human vision, it remains unclear how much they actually matter for subsequent performance. Here, we explore the possibility that shape skeletons help mediate the ability to extract visual similarity. Observers completed a same/different task in which two shapes could vary either in their skeletal structure (without changing superficial features such as size, orientation, and internal angular separation) or in large surface-level ways (without changing overall skeletal organization). Discrimination was better for skeletally dissimilar shapes: observers had difficulty appreciating even surprisingly large differences when those differences did not reorganize the underlying skeletons. This pattern also generalized beyond line drawings to 3-D volumes whose skeletons were less readily inferable from the shapes’ visible contours. These results show how shape skeletons may influence the perception of similarity—and more generally, how they have important consequences for downstream visual processing.

     

Processing sets of letters for order: Evidence from reaction time experiments

In two experiments, subjects were required to impose different levels of organization on randomly ordered letters. In a between-subject design, the subject was to identify the letter in the set coming first in the alphabet or to reorganize the set into an alphabetic sequence. In a within-subject design, presentation of the letters was followed by an instruction to carry out the identification or reorganization task or to recite the letters in left-to-right order. Reaction time varied systematically with level of required organization, size of the presented set, and position and spacing of the letter set in the alphabet. The results are discussed in terms of two simple models.     

Curious Objects: How Visual Complexity Guides Attention and Engagement

Some things look more complex than others. For example, a crenulate and richly organized leaf may seem more complex than a plain stone. What is the nature of this experience—and why do we have it in the first place? Here, we explore how object complexity serves as an efficiently extracted visual signal that the object merits further exploration. We algorithmically generated a library of geometric shapes and determined their complexity by computing the cumulative surprisal of their internal skeletons—essentially quantifying the “amount of information” within each shape—and then used this approach to ask new questions about the perception of complexity. Experiments 1–3 asked what kind of mental process extracts visual complexity: a slow, deliberate, reflective process (as when we decide that an object is expensive or popular) or a fast, effortless, and automatic process (as when we see that an object is big or blue)? We placed simple and complex objects in visual search arrays and discovered that complex objects were easier to find among simple distractors than simple objects are among complex distractors—a classic search asymmetry indicating that complexity is prioritized in visual processing. Next, we explored the function of complexity: Why do we represent object complexity in the first place? Experiments 4–5 asked subjects to study serially presented objects in a self-paced manner (for a later memory test); subjects dwelled longer on complex objects than simple objects—even when object shape was completely task-irrelevant—suggesting a connection between visual complexity and exploratory engagement. Finally, Experiment 6 connected these implicit measures of complexity to explicit judgments. Collectively, these findings suggest that visual complexity is extracted efficiently and automatically, and even arouses a kind of “perceptual curiosity” about objects that encourages subsequent attentional engagement.     

When do ratings implicate perception versus judgment? The “overgeneralization test” for top-down effects

ABSTRACT

When looking at an object—say, a banana—we can both directly perceive its visual qualities (e.g., its size) and also make higher-level judgments about its visual and non-visual properties (e.g., not only its size, but also its cost). Suppose you obtain a rating of a property such as size. Does that rating implicate seeing or merely higher-level judgment? The answer often matters a great deal -- e.g., determining whether such ratings imply “top-down” effects of cognition on perception. Too often, however, this distinction is ignored in empirical investigations of such effects. Here we suggest a simple test for when such ratings can be used to implicate perception: whenever the very same experiment “overgeneralizes” to an unambiguously non-perceptual factor, the results cannot be used to draw implications about perception, per se. As a case study, we investigate an empirical report alleging that conservatives perceive Barack Obama as darker skinned than liberals do. Two simple experiments show that the very same effects, measured via the same “representativeness” ratings, obtain with unambiguously non-perceptual and even silly factors (involving bright red horns vs. halos, rather than brightness differences). We suggest that this renders such methods unable to implicate visual processing and we recommend that “overgeneralization tests” of this type always be conducted in such contexts.     

Revenge without responsibility? Judgments about collective punishment in baseball

Many cultures practice collective punishment; that is, they will punish one person for another's transgression, based solely on shared group membership. This practice is difficult to reconcile with the theories of moral responsibility that dominate in contemporary Western psychology, philosophy and law. Yet, we demonstrate a context in which many American participants do endorse collective punishment: retaliatory “beaning” in baseball. Notably, individuals who endorse this form of collective punishment tend not to hold the target of retaliation to be morally responsible. In other words, the psychological mechanisms underlying such “vicarious” forms of collective punishment appear to be distinct from the evaluation of moral responsibility. Consequently, the observation of collective punishment in non-Western cultures may not indicate the operation of fundamentally different conceptions of moral responsibility.     

English letter frequencies and their applications: part I

This article presents data regarding the relative frequencies of single letters in English, organized by word length and letter position. Derived from a parsimonious sample of English word use patterns presented by Whissell in 1998, the data accurately represent letter frequencies found in modern English. These data provide a resource for various applications, including reading research and practice.