Parts and Wholes in Face Recognition

TLDR

Prior research suggests that face recognition may rely on holistic representations, with parts identified more easily only when they are explicitly represented in a hierarchical visual system. The study tests whether face recognition is holistic by predicting that parts of faces are more easily recognized within the whole face than in isolation, compared to other stimuli. The authors interpret existing evidence and design new empirical tests based on a definition of holistic representation as lacking internal part structure. Across three experiments, participants identified facial parts more accurately within whole faces than in isolation, whereas scrambled faces, inverted faces, and houses showed no such advantage.

Abstract

Are faces recognized using more holistic representations than other types of stimuli? Taking holistic representation to mean representation without an internal part structure, we interpret the available evidence on this issue and then design new empirical tests. Based on previous research, we reasoned that if a portion of an object corresponds to an explicitly represented part in a hierarchical visual representation, then when that portion is presented in isolation it will be identified relatively more easily than if it did not have the status of an explicitly represented part. The hypothesis that face recognition is holistic therefore predicts that a part of a face will be disproportionately more easily recognized in the whole face than as an isolated part, relative to recognition of the parts and wholes of other kinds of stimuli. This prediction was borne out in three experiments: subjects were more accurate at identifying the parts of faces, presented in the whole object, than they were at identifying the same part presented in isolation, even though both parts and wholes were tested in a forced-choice format and the whole faces differed only by one part. In contrast, three other types of stimuli--scrambled faces, inverted faces, and houses--did not show this advantage for part identification in whole object recognition.