We present a method for creating black-and-white illustrations from photographs of human faces. In addition an interactive technique is demonstrated for deforming these black-and-white facial illustrations to create caricatures which highlight and exaggerate representative facial features. We evaluate the effectiveness of the resulting images through psychophysical studies to assess accuracy and speed in both recognition and learning tasks. These studies show that the facial illustrations and caricatures generated using our techniques are as effective as photographs in recognition tasks. For the learning task we find that illustrations are learned two times faster than photographs and caricatures are learned one and a half times faster than photographs. Because our techniques produce images that are effective at communicating complex information, they are useful in a number of potential applications, ranging from entertainment and education to low bandwidth telecommunications and psychology research. Categories and Subject Descriptors: I.3.3 [Computer Graphics]: Picture/image Generation—bitmap and framebuffer operations;

Here we review recent findings that reveal the functional properties of extra-striate regions in the human visual cortex that are involved in the representation and perception of objects. We characterize both the invariant and non-invariant properties of these regions and we discuss the correlation between activation of these regions and recognition. Overall, these results indicate that the lateral occipital complex plays an important role in human object recognition.

Three theories currently compete to explain the conceptual deficits that result from brain damage: sensory-functional theory, domain-specific theory, and conceptual structure theory. We argue that all three theories capture important aspects of conceptual deficits, and offer different insights into their origins. Conceptual topography theory (CTT) integrates these insights, beginning with A. R. Damasio’s (1989) convergence zone theory and elaborating it with the similarity-in-topography (SIT) principle. According to CTT, feature maps in sensory-motor systems represent the features of a category’s exemplars. A hierarchical system of convergence zones then conjoins these features to form both property and category representations. According to the SIT principle, the proximity of two conjunctive neurons in a convergence zone increases with the similarity of the features they conjoin. As a result, conjunctive neurons become topographically organised into local regions that represent properties and categories. Depending on the level and location of a lesion in this system, a wide variety of deficits is possible. Consistent with the literature, these deficits range from the loss of a single category to the loss of multiple categories that share sensory-motor properties.

There is strong evidence that face processing in the brain is localized. The double dissociation between prosopagnosia, a face recognition deficit occurring after brain damage, and visual object agnosia, difficulty recognizing other kinds of complex objects, indicates that face and non-face object recognition may be served by partially independent neural mechanisms. In this paper, we use computational models to show how the face processing specialization apparently underlying prosopagnosia and visual object agnosia could be attributed to (1) a relatively simple competitive selection mechanism that, during development, devotes neural resources to the tasks they are best at performing, (2) the developing infant's need to perform subordinate classification (identification) of faces early on, and (3) the infant's low visual acuity at birth. Inspired by de Schonen, Mancini and Liegeois' arguments (1998) [de Schonen, S., Mancini, J., Liegeois, F. (1998). About functional cortical specializat...

Although most adults are considered to be experts in the identification of faces, fewer people specialize in the recognition of other objects, such as birds and dogs. In this research, the neurophysiological processes associated with expert bird and dog recognition were investigated using event-related potentials. An enhanced early negative component (N170, 164 ms) was found when bird and dog experts categorized objects in their domain of expertise relative to when they categorized objects outside their domain of expertise. This finding indicates that objects from well-learned categories are neurologically differentiated from objects from lesser-known categories at a relatively early stage of visual processing.

Most systems used for creating and displaying colormap-based visualizations are not photometrically calibrated. That is, the relationship between RGB input levels and perceived luminance is usually not known, due to variations in the monitor, hardware configuration, and the viewing environment. However, the luminance component of perceptually based colormaps should be controlled, due to the central role that luminance plays in our visual processing. We address this problem with a simple and effective method for performing luminance matching on an uncalibrated monitor. The method is akin to the minimally distinct border technique (a previous method of luminance matching used for measuring luminous efficiency), but our method relies on the brain's highly developed ability to distinguish human faces. We present a user study showing that our method produces equivalent results to the minimally distinct border technique, but with significantly improved precision. We demonstrate how results from our luminance matching method can be directly applied to create new univariate colormaps.

this article, reporting the results of multiple psychophysical experiments during the acquisition of expertise with novel objects. To leverage these methods, our approach combines psychophysical assessment with neuroimaging techniques in two ways. First, the psychophysical procedure we used to train participants to expertise was the same as that used in a recent neuroimaging study, in which activity for Greebles in the fusiform face area (FFA) increased with expertise (Gauthier, Tarr, Anderson, Skudlarski, & Gore, 1999; half of the 10 participants in the present study also participated in this earlier fMRI study). Second, we correlated behavioral measures of expertise acquisition with concurrent neural changes in these same participants

Evidence from fields as diverse as cognitive, evolutionary, and developmental psychology, as well as cognitive neuroscience, has increasingly pointed to the ‘special ’ nature of face recognition. A critical examination of the literature supports the view that faces begin to be seen as a separate class of objects within the first 6 months of life. Not surprisingly, the neural systems that underlie face recognition also come on line during this period of time. Less clear, however, are the mechanisms whereby these events occur. It seems likely that face recognition reflects an experience-expectant process, whereby exposure to faces during a sensitive period of development likely leads to perceptual and cortical specialization. However, it is unknown what the role of experience is in maintaining this ability, and how long this sensitive period lasts. After reviewing three related models that attempt to account for the way the ability to recognize faces

Our mental representation of object categories is hierarchically organized, and our rapid and seemingly effortless categorization ability is crucial for our daily behavior. Here, we examine responses of a large number (>600) of neurons in monkey inferior temporal (IT) cortex with a large number (>1000) of natural and artificial object images. During the recordings the monkeys performed a passive fixation task. We found that the categorical structure of objects is represented by the pattern of activity distributed over the cell population. Animate and inanimate objects created distinguishable clusters in the population code.

Recognizing emotion from facial expressions draws on diverse psychological processes implemented in a large array of neural structures. Studies using evoked potentials, lesions, and functional imaging have begun to elucidate some of the mechanisms. Early perceptual processing of faces draws on cortices in occipital and temporal lobes that construct detailed representations from the configuration of facial features. Subsequent recognition requires a set of structures, including amygdala and orbitofrontal cortex, that links perceptual representations of the face to the generation of knowledge about the emotion signaled, a complex set of mechanisms using multiple strategies. Although recent studies have provided a wealth of detail regarding these mechanisms in the adult human brain, investigations are also being extended to nonhuman primates, to infants, and to patients with psychiatric disorders.