Size Effects in the Recognition of Blurry Faces

Recognizing distant faces

As an 'early alerting' sense, one of the primary tasks for the human visual system is to recognize distant objects. In the specific context of facial identification, this ecologically important task has received surprisingly little attention. Most studies have investigated facial recognition at short, fixed distances. Under these conditions, the photometric and configural information related to the eyes, nose and mouth are typically found to be primary determinants of facial identity. Here we characterize face recognition performance as a function of viewing distance and investigate whether the primacy of the internal features continues to hold across increasing viewing distances. We find that exploring the distance dimension reveals a qualitatively different salience distribution across a face. Observers' recognition performance significantly exceeds that obtained with the internal facial physiognomy, and also exceeds the computed union of performances with internal and external features alone, suggesting that in addition to the mutual configuration of the eyes, nose and mouth, it is the relationships between these features and external head contours that are crucial for recognition. We have also conducted computational studies with convolutional neural networks trained on the task of face recognition to examine whether this representational bias could emerge spontaneously through exposure to faces. The results provide partial support for this possibility while also highlighting important differences between the human and artificial system. These findings have implications for the nature of facial representations useful for a visual system, whether human or machine, for recognition over large and varying distances.

Coarse-to-Fine(r) Automatic Familiar Face Recognition in the Human Brain

At what level of spatial resolution can the human brain recognize a familiar face in a crowd of strangers? Does it depend on whether one approaches or rather moves back from the crowd? To answer these questions, 16 observers viewed different unsegmented images of unfamiliar faces alternating at 6 Hz, with spatial frequency (SF) content progressively increasing (i.e., coarse-to-fine) or decreasing (fine-to-coarse) in different sequences. Variable natural images of celebrity faces every sixth stimulus generated an objective neural index of single-glanced automatic familiar face recognition (FFR) at 1 Hz in participants' electroencephalogram (EEG). For blurry images increasing in spatial resolution, the neural FFR response over occipitotemporal regions emerged abruptly with additional cues at about 6.3-8.7 cycles/head width, immediately reaching amplitude saturation. When the same images progressively decreased in resolution, the FFR response disappeared already below 12 cycles/head width, thus providing no support for a predictive coding hypothesis. Overall, these observations indicate that rapid automatic recognition of heterogenous natural views of familiar faces is achieved from coarser visual inputs than generally thought, and support a coarse-to-fine FFR dynamics in the human brain.

Face perception: A brief journey through recent discoveries and current directions

Faces are a rich source of information about the people around us. Identity, state of mind, emotions, intentions, age, gender, ethnic background, attractiveness and a host of other attributes about an individual can be gleaned from a face. When face perception fails, dramatic psycho-social consequences can follow at the individual level, as in the case of prosopagnosic parents who are unable to recognize their children at school pick-up. At the species level, social interaction patterns are shaped by human face perception abilities. The computational feat of recognizing faces and facial attributes, and the challenges overcome by the human brain to achieve this feat, have fascinated generations of vision researchers. In this paper, we present a brief overview of some of the milestones of discovery as well as outline a selected set of current directions and open questions on this topic.