Face detection in contextual scenes.

Object and scene perception are intertwined. When objects are expected to appear within a particular scene, they are detected and categorised with greater speed and accuracy. This study examined whether such context effects also moderate the perception of social objects such as faces. Female and male faces were embedded in scenes with a stereotypical female or male context. Semantic congruency of these scene contexts influenced the categorisation of faces (Experiment 1). These effects were bi-directional, such that face sex also affected scene categorisation (Experiment 2), suggesting concurrent automatic processing of both levels. In contrast, the more elementary task of face detection was not affected by semantic scene congruency (Experiment 3), even when scenes were previewed prior to face presentation (Experiment 4). This pattern of results indicates that semantic scene context can affect categorisation of faces. However, the earlier perceptual stage of detection appears to be encapsulated from the cognitive processes that give rise to this contextual interference.

A cognitive template for human face detection.

Faces are highly informative social stimuli, yet before any information can be accessed, the face must first be detected in the visual field. A detection template that serves this purpose must be able to accommodate the wide variety of face images we encounter, but how this generality could be achieved remains unknown. In this study, we investigate whether statistical averages of previously encountered faces can form the basis of a general face detection template. We provide converging evidence from a range of methods-human similarity judgements and PCA-based image analysis of face averages (Experiment 1-3), human detection behaviour for faces embedded in complex scenes (Experiment 4 and 5), and simulations with a template-matching algorithm (Experiment 6 and 7)-to examine the formation, stability and robustness of statistical image averages as cognitive templates for human face detection. We integrate these findings with existing knowledge of face identification, ensemble coding, and the development of face perception.

Ingroup and outgroup differences in face detection.

Humans show improved recognition for faces from their own social group relative to faces from another social group. Yet before faces can be recognized, they must first be detected in the visual field. Here, we tested whether humans also show an ingroup bias at the earliest stage of face processing - the point at which the presence of a face is first detected. To this end, we measured viewers' ability to detect ingroup (Black and White) and outgroup faces (Asian, Black, and White) in everyday scenes. Ingroup faces were detected with greater speed and accuracy relative to outgroup faces (Experiment 1). Removing face hue impaired detection generally, but the ingroup detection advantage was undiminished (Experiment 2). This same pattern was replicated by a detection algorithm using face templates derived from human data (Experiment 3). These findings demonstrate that the established ingroup bias in face processing can extend to the early process of detection. This effect is 'colour blind', in the sense that group membership effects are independent of general effects of image hue. Moreover, it can be captured by tuning visual templates to reflect the statistics of observers' social experience. We conclude that group bias in face detection is both a visual and a social phenomenon.

Capacity limits in face detection.

Face detection is a prerequisite for further face processing, such as extracting identity or semantic information. Those later processes appear to be subject to strict capacity limits, but the location of the bottleneck is unclear. In particular, it is not known whether the bottleneck occurs before or after face detection. Here we present a novel test of capacity limits in face detection. Across four behavioural experiments, we assessed detection of multiple faces via observers' ability to differentiate between two types of display. Fixed displays comprised items of the same type (all faces or all non-faces). Mixed displays combined faces and non-faces. Critically, a 'fixed' response requires all items to be processed. We found that additional faces could be detected with no cost to efficiency, and that this capacity-free performance was contingent on visual context. The observed pattern was not specific to faces, but detection was more efficient for faces overall. Our findings suggest that strict capacity limits in face perception occur after the detection step.