Subordinate Level Classification and Face Perception

In addition to the psychophysical experiments reviewed earlier, a second collection of behavioral experiments has examined the relative ease of object perception when stimuli must be identified at different classification levels. The entry level for any given object is operationally defined as the first name that comes to mind for that object (e.g., dog); subordinatate-level labels are more specific (beagle), and superordinate labels are more general (animal). Numerous studies have demonstrated that common objects are easiest to classify at the entry level. These experiments typically use a label verification task, in which a word is followed by a picture of an object on each trial and the subject decides whether the word and picture match. Response times are faster and error rates lower for entry-level than for suborinate- and superordinate-level labels.

It is generally held that this entry-level advantage is at least partially perceptual in nature, that is, object perception processes are specialized to produce representations that are most efficient for identifying objects at the entry level. Neuroimaging studies have supported this assumption by showing that the extra time taken to identify objects at the subordinate level is due to additional processing by the visual system, presumably supplementing the object perception processes that allow for entry-level identification.

The most subordinate level of identification is the individual level (Snoopy), and, as mentioned already, a large literature is devoted to individual-level recognition of one particular class of objects: faces. Much of this literature is dedicated to demonstrating that face perception involves qualitatively different processes than the perception of other objects. The most well-known finding in this regard is the inversion effect. As already discussed, almost all objects are more difficult to recognize when inverted (turned upside down) than when upright, but the increase in difficulty for faces is especially pronounced. Faces are also more difficult to recognize than other objects when the top and bottom halves of images are misaligned (Fig. 7 demonstrates both the inversion and misalignment effects).

Although there are a number of hypotheses concerning exactly how faces are processed, most agree on the basic premise that a precise specification of the configuration of face parts is crucial for face perception. In other words, a face representation must include not just the information that the nose is ABOVE the mouth but must specify the exact distance by which these parts are separated. Such precision is not necessary to discriminate between members of most other classes of objects, such as the chairs in Fig. 7.

Figure 7 Face perception can be dissociated from the perception of other classes of objects by a number of behavioral effects, two of which are demonstrated here. It is quite difficult to pick out the upright faces in the bottom left triad of images that match the inverted and misaligned faces in the upper left of the figure. By contrast, matching upright with inverted and misaligned chairs is relatively easy, as shown at right.

Figure 7 Face perception can be dissociated from the perception of other classes of objects by a number of behavioral effects, two of which are demonstrated here. It is quite difficult to pick out the upright faces in the bottom left triad of images that match the inverted and misaligned faces in the upper left of the figure. By contrast, matching upright with inverted and misaligned chairs is relatively easy, as shown at right.

Many researchers believe that configural processing is carried out in the anterior fusiform face area identified in the neuroimaging studies described earlier. A lively debate is currently underway in the literature concerning the nature of the processing going on in this area, most crucially whether it is a truly face-specific processing system or whether it instead can contribute to the recognition of other objects at subordinate levels. Prosopagnosic patients can recognize some types of objects at subordinate levels (one patient was even able to learn to recognize individuals from his flock of pet sheep), but careful testing shows that they are generally poorer at subordinate- than at entry-level identification.

Other research points to expertise as a crucial factor in face-specific behavioral effects. Dog show judges and bird watchers show inversion and other face-specific effects for their domains of expertise, and exciting research has shown the anterior fusiform responding preferentially to a class of novel objects only after subjects were trained to be experts at recognizing these objects at the individual level. All normally developing humans are face perception experts, so it is possible that the anterior fusiform is specialized for processing any class of objects that is both recognized at a highly subordinate level and highly overlearned. Whether this processing involves representations that are qualitatively or only quantitatively different from those involved in entry-level object perception remains a subject for future research.

See Also the Following Articles

ARTIFICIAL INTELLIGENCE • ATTENTION • CONSCIOUSNESS • INFORMATION PROCESSING • MEMORY, NEUROIMAGING • MOTION PROCESSING • MULTISENSORY INTEGRATION • PATTERN RECOGNITION • PROSOPAGNOSIA • SALIENCE • SPATIAL COGNITION

Suggested Reading

Biederman, I. (1987). Recognition-by-components: A theory of human image understanding. Psychol. Rev. 94, 115-147. Farah, M. J. (1990). Visual agnosia: Disorders of Object Recognition and What They Tell Us about Normal Vision. MIT Press, Cambridge, MA. Marr, D. (1982). Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. Freeman, San Fransisco. Palmer, S. E. (1999). Vision Science: Photons to Phenomenology.

MIT Press, Cambridge, MA. Tarr, M. J., and Pinker, S. (1989). Mental rotation and orientation dependence in shape recognition. Cogn. Psychol. 21, 233-282. Ullman, S. (1996). High Level Vision. MIT Press, Cambridge, MA.

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