To understand visual consciousness, we must understand how the brain represents ensembles of objects at many levels of perceptual analysis. Ensemble perception refers to the visual system's ability to extract summary statistical information from groups of similar objects-often in a brief glance. It defines foundational limits on cognition, memory, and behavior. In this review, we provide an operational definition of ensemble perception and demonstrate that ensemble perception spans across multiple levels of visual analysis, incorporating both low-level visual features and high-level social information. Further, we investigate the functional usefulness of ensemble perception and its efficiency, and we consider possible physiological and cognitive mechanisms that underlie an individual's ability to make accurate and rapid assessments of crowds of objects.

The perception of attractiveness is essential for choices of food, object, and mate preference. Like perception of other visual features, perception of attractiveness is stable despite constant changes of image properties due to factors like occlusion, visual noise, and eye movements. Recent results demonstrate that perception of low-level stimulus features and even more complex attributes like human identity are biased towards recent percepts. This effect is often called serial dependence. Some recent studies have suggested that serial dependence also exists for perceived facial attractiveness, though there is also concern that the reported effects are due to response bias. Here we used an attractiveness-rating task to test the existence of serial dependence in perceived facial attractiveness. Our results demonstrate that perceived face attractiveness was pulled by the attractiveness level of facial images encountered up to 6 s prior. This effect was not due to response bias and did not rely on the previous motor response. This perceptual pull increased as the difference in attractiveness between previous and current stimuli increased. Our results reconcile previously conflicting findings and extend previous work, demonstrating that sequential dependence in perception operates across different levels of visual analysis, even at the highest levels of perceptual interpretation.

Much of the richness of perception is conveyed by implicit, rather than image or feature-level, information. The perception of animacy or lifelikeness of objects, for example, cannot be predicted from image level properties alone. Instead, perceiving lifelikeness seems to be an inferential process and one might expect it to be cognitively demanding and serial rather than fast and automatic. If perceptual mechanisms exist to represent lifelikeness, then observers should be able to perceive this information quickly and reliably, and should be able to perceive the lifelikeness of crowds of objects. Here, we report that observers are highly sensitive to the lifelikeness of random objects and even groups of objects. Observers' percepts of crowd lifelikeness are well predicted by independent observers' lifelikeness judgements of the individual objects comprising that crowd. We demonstrate that visual impressions of abstract dimensions can be achieved with summary statistical representations, which underlie our rich perceptual experience.

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