Facial Composites

When a crime has been committed and the identity of the perpetrator is unknown, eyewitnesses are often asked to attempt to create a likeness of the face of the perpetrator. An eyewitness can do this by creating a facial composite, either through the assistance of a sketch artist or by using a mechanized composite system. However, facial composites tend to be poor representations of the intended face, even if it is a face that is very familiar to the composite creator. This is probably due to a mismatch between the way in which people encode faces and the way in which they attempt to recall faces when building a composite.

When facial composites were first introduced in the criminal justice system, eyewitnesses would work together with a sketch artist to create a likeness of the intended face. Today, law enforcement agencies typically use mechanized composite production systems, and computerized composite production systems are used more than twice as often as noncomputerized versions. The original mechanized composite production systems, such as the Identi-Kit and Photo-Fit, are composed of overlays of facial features (e.g., noses, eyes, chins, hair) that can be combined to create a face. Modern, computerized versions, such as E-fit, Mac-a-Mug, and FACES, consist of features that can be combined, and typically resized, in any order to create a face. Currently, however, composite production systems are being created that move away from producing a face at the feature level and, instead, focus on whole faces.

Many of the mechanized and computerized systems have attempted to increase the number of features available from which a composite creator may choose, the realism of the final product, and the user friendliness of the interface. FACES, for example, has more than 3,700 features, ranging from relatively prominent features such as hair, eyes, and lips to detailed features such as eye lines and mouth lines. The computerized systems result in a fairly realistic product and can be used after a minimal training session. However, even when people view a face that has been created with a composite system and attempt to re-create the face using the same system, thereby ensuring that all the features are available, they are still unable to create good likenesses of the intended face. Furthermore, composite producers themselves are poor judges of how well the composite that they have created matches the target face. Even if a person who creates a composite rates the composite's similarity to the face that it is intended to represent, this rating is not predictive of how others rate the similarity of the composite to the target face.

Researchers have typically assessed people's ability to create composites of faces through naming tasks, matching tasks, and similarity-rating tasks. Naming tasks show people a composite of someone who should be familiar to them (e.g., a famous person) and ask them to name the person the composite is designed to depict. Matching tasks have people choose which face the composite is designed to depict from a larger set of faces. Similarity-rating tasks have people rate the similarity between a composite and the face it is designed to depict. In general, facial composites tend to be poor likenesses of the faces that they [Page 306]are intended to represent, regardless of the composite production system and regardless of how the similarity of the composite to the intended face is assessed.

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