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Biomedical subjects

P G Schyns

Publications and source records attributed to P G Schyns.

11 recordsLinked to original sources

Is high-spatial frequency information used in the early stages of face detection?

The present study examined the role of high-spatial frequency information in early face processing, as indexed by the N170 face-sensitive ERP component. Participants detected 4 versions of famous faces, including full spectrum faces, and bandpass filtered faces containing predominantly high-spatial frequencies, low-spatial frequencies or both. The power spectra of all stimuli were balanced by superimposing the faces onto a visual noise background that included the spatial frequency information that was missing in filtered faces, e.g., high-spatial frequency faces were presented on a high- and low-spatial frequency background. An additional condition comprising of filtered visual noise only was also created to ensure that any observed effects were related to the processing of faces and not simply due to variations between spatial frequency information. Both behavioral and electrophysiological results replicated previous findings of a low-spatial frequency advantage for face processing. However, our results also show that faces containing both high and low-spatial frequency information are detected faster and more accurately than faces containing predominantly low-spatial frequencies. Furthermore, this advantage occurred with an enhanced amplitude of the N170. Together, these findings refute the suggestion that high-spatial frequencies are redundant in face perception.

Adult↗

Bubbles: a technique to reveal the use of information in recognition tasks.

Everyday, people flexibly perform different categorizations of common faces, objects and scenes. Intuition and scattered evidence suggest that these categorizations require the use of different visual information from the input. However, there is no unifying method, based on the categorization performance of subjects, that can isolate the information used. To this end, we developed Bubbles, a general technique that can assign the credit of human categorization performance to specific visual information. To illustrate the technique, we applied Bubbles on three categorization tasks (gender, expressive or not and identity) on the same set of faces, with human and ideal observers to compare the features they used.

Facial Expression↗

Why do we SLIP to the basic level? Computational constraints and their implementation.

The authors introduce a new measure of basic-level performance (strategy length and internal practicability; SLIP). SLIP implements 2 computational constraints on the organization of categories in a taxonomy: the minimum number of feature tests required to place the input in a category (strategy length) and the ease with which these tests are performed (internal practicability). The predictive power of SLIP is compared with that of 4 other basic-level measures: context model, category feature possession, category utility, and compression measure, drawing data from other empirical work, and 3 new experiments testing the validity of the computational constraints of SLIP using computer-synthesized 3-dimensional artificial objects.

Adult↗

Usage of spatial scales for the categorization of faces, objects, and scenes.

The role of spatial scales (or spatial frequencies) in the processing of faces, objects, and scenes has recently seen a surge of research activity. In this review, we will critically examine two main theories of scale usage. The fixed theory proposes that spatial scales are used in a fixed, perceptually determined order (coarse to fine). The flexible theory suggests instead that usage of spatial scales is flexible, depending on the requirements of visual information for the categorization task at hand. The implications of the theories are examined for face, object, and scene categorization, attention, perception, and representation.

Cognition↗

Diagnostic colors mediate scene recognition.

In this research, we aim to ground scene recognition on information other than the identity of component objects. Specifically we seek to understand the structure of color cues that allows the express recognition of scene gists. Using the L*a*b* color space we examined the conditions under which chromatic cues concur with brightness to allow a viewer to recognize scenes at a glance. Using different methods, Experiments 1 and 2 tested the hypothesis that colors do contribute when they are diagnostic (i.e., predictive) of a scene category. Experiment 3 examined the structure of colored cues at different spatial scales that are responsible for the effects of color diagnosticity reported in Experiments 1 and 2. Together, the results suggest that colored blobs at a coarse spatial scale concur with luminance cues to form the relevant spatial layout that mediates express scene recognition.

Adult↗

Dr. Angry and Mr. Smile: when categorization flexibly modifies the perception of faces in rapid visual presentations.

Are categorization and visual processing independent, with categorization operating late, on an already perceived input, or are they intertwined, with the act of categorization flexibly changing (i.e. cognitively penetrating) the early perception of the stimulus? We examined this issue in three experiments by applying different categorization tasks (gender, expressive or not, which expression and identity) to identical face stimuli. Stimuli were hybrids: they combined a man or a woman with a particular expression at a coarse spatial scale with a face of the opposite gender with a different expression at the fine spatial scale. Results suggested that the categorization task changes the spatial scales preferentially used and perceived for rapid recognition. A perceptual set effect is shown whereby the scale preference of an important categorization (e.g. identity) transfers to resolve other face categorizations (e.g. expressive or not, which expression). Together, the results suggest that categorization can be closely bound to perception.

Adolescent↗

Diagnostic recognition: task constraints, object information, and their interactions.

Object recognition and categorization research are both concerned with understanding how input information matches object information in memory. It is therefore surprising that these two fields have evolved independently, without much cross-fertilization. It is the main objective of this paper to lay out the basis of a dialogue between object recognition and categorization research, with the hope of raising issues that could cross-fertilize both domains. To this end, the paper develops diagnostic recognition, a framework which formulates recognition performance as an interaction of task constraints and object information. I argue and present examples suggesting that diagnostic recognition could be fruitfully applied to the understanding of everyday object recognition. Issues are raised regarding the psychological status of the interactions specified in the framework.

Attention↗

The development of features in object concepts.

According to one productive and influential approach to cognition, categorization, object recognition, and higher level cognitive processes operate on a set of fixed features, which are the output of lower level perceptual processes. In many situations, however, it is the higher level cognitive process being executed that influences the lower level features that are created. Rather than viewing the repertoire of features as being fixed by low-level processes, we present a theory in which people create features to subserve the representation and categorization of objects. Two types of category learning should be distinguished. Fixed space category learning occurs when new categorizations are representable with the available feature set. Flexible space category learning occurs when new categorizations cannot be represented with the features available. Whether fixed or flexible, learning depends on the featural contrasts and similarities between the new category to be represented and the individuals existing concepts. Fixed feature approaches face one of two problems with tasks that call for new features: If the fixed features are fairly high level and directly useful for categorization, then they will not be flexible enough to represent all objects that might be relevant for a new task. If the fixed features are small, subsymbolic fragments (such as pixels), then regularities at the level of the functional features required to accomplish categorizations will not be captured by these primitives. We present evidence of flexible perceptual changes arising from category learning and theoretical arguments for the importance of this flexibility. We describe conditions that promote feature creation and argue against interpreting them in terms of fixed features. Finally, we discuss the implications of functional features for object categorization, conceptual development, chunking, constructive induction, and formal models of dimensionality reduction.

Child↗

Coarse blobs or fine edges? Evidence that information diagnosticity changes the perception of complex visual stimuli.

Efficient categorizations of complex visual stimuli require effective encodings of their distinctive properties. However, the question remains of how processes of object and scene categorization use the information associated with different perceptual spatial scales. The psychophysics of scale perception suggests that recognition uses coarse blobs before fine scale edges, because the former is perceptually available before the latter. Although possible, this perceptually determined scenario neglects the nature of the task the recognition system must solve. If different spatial scales transmit different information about the input, an identical scene might be flexibly encoded and perceived at the scale that optimizes information for the considered task-i.e., the diagnostic scale. This paper tests the hypothesis that scale diagnosticity can determine scale selection for recognition. Experiment 1 tested whether coarse and fine spatial scales were both available at the onset of scene categorization. The second experiment tested that the selection of one scale could change depending on the diagnostic information present at this scale. The third and fourth experiments investigated whether scale-specific cues were independently processed, or whether they perceptually cooperated in the recognition of the input scene. Results suggest that a mandatory low-level registration of multiple spatial scales promotes flexible scene encodings, perceptions, and categorizations.

Adult↗

Information and viewpoint dependence in face recognition.

How we recognize faces despite rotations in depth is of great interest to psychologists, computer scientists and neurophysiologists because of the accuracy of human performance despite the intrinsic difficulty of the task. Three experiments are reported here which used three-dimensional facial surface representations to investigate the effects of rotations in depth on a face recognition task. Experiment 1, using "shape only" representations, showed that all the views used (full-face, three-quarter and profile) were equally well recognized when all had been learned. Performance was better when the same views were presented in an animated sequence rather than at random, suggesting that structure-from-motion provides useful information for recognition. When stimuli were presented inverted, performance was worse and there were differences in the recognizability of views, demonstrating that the familiarity of upright faces affects generalization across views. Experiments 2 and 3 investigated generalization from single views and found performance to be dependent on learned view. In both experiments, generalization from learned full-face fell off with increasing angle of rotation. With shape only stimuli, three-quarter views generalized well to each other, even when inverted but for profiles generalization was equally bad to all unlearned views. This difference may be explained because of the particular relationship of the profile to the axis of symmetry. In Experiment 3, addition of information about superficial properties including color and texture facilitated performance, but patterns of generalization remained substantially the same, emphasizing the importance of underlying shape information. However, generalization from the three-quarter view became viewpoint invariant and there was some evidence for better generalization between profiles. The results are interpreted as showing that three-dimensional shape information is fundamental for recognition across rotations in depth although superficial information may also be used to reduce viewpoint dependence.

Adult↗

Flexible, diagnosticity-driven, rather than fixed, perceptually determined scale selection in scene and face recognition.

Different classifications of an identical visual stimulus may require different perceptual properties from the visual input. How do processes of object and scene categorisation use the information associated with different perceptual spatial scales? One scenario suggests that recognition should use coarse blobs before fine-scale edges because scale usage is perceptually determined. However, perceptual determination neglects one important aspect of any recognition task: the information demands of the considered classification of the input. Evidence is reviewed suggesting that scale usage could be flexibly determined by the diagnosticity of scale-specific cues for different categorisations of scenes and faces.

Face↗