Finding faces, animals, and vehicles in far peripheral vision

Abstract

Neuroimaging studies have shown that faces exhibit a central visual field bias, as compared to buildings and scenes. With a saccadic choice task, Crouzet, Kirchner, and Thorpe (2010) demonstrated a speed advantage for the detection of faces with stimuli located 8° from fixation. We used the same paradigm to examine whether the face advantage, relative to other categories (animals and vehicles), extends across the whole visual field (from 10° to 80° eccentricity) or whether it is limited to the central visual field. Pairs of photographs of natural scenes (a target and a distractor) were displayed simultaneously left and right of central fixation for 1s on a panoramic screen. Participants were asked to saccade to a target stimulus (faces, animals, or vehicles). The distractors were images corresponding to the two other categories. Eye movements were recorded with a head-mounted eye tracker. Only the first saccade was measured. Experiment 1 showed that (a) in terms of speed of categorization, faces maintain their advantage over animals and vehicles across the whole visual field, up to 80° and (b) even in crowded conditions (an object embedded in a scene), performance was above chance for the three categories of stimuli at 80° eccentricity. Experiment 2 showed that, when compared to another category with a high degree of within category structural similarity (cars), faces keep their advantage at all eccentricities. These results suggest that the bias for faces is not limited to the central visual field, at least in a categorization task.

Object categorization in visual periphery is modulated by delayed foveal noise

“…However, some recent studies have shown that peripheral vision is able to perform rapid scene categorization tasks (Boucart, Moroni, Thibaut, et al, 2013;Larson & Loschky, 2009) and to solve complex object categorization tasks including natural object discrimination (Boucart et al, 2010;Boucart, Moroni, Szaffarczyk, & Tran, 2013;Ehinger & Rosenholtz, 2016;S. J. Thorpe et al, 2001) and face recognition (Crouzet, Kirchner, & Thorpe, 2010;Hershler, Golan, Bentin, & Hochstein, 2010) in the very far periphery (Boucart et al, 2016). Moreover, recent neuroimaging findings in humans have suggested that there is a feedback system in the brain that somehow sends the information from visual periphery to cortical regions retinotopic to fovea (Chambers et al, 2013;M.…”

“…Recent studies have shown that human subjects can accurately categorize peripherally presented object and face images at highly abstract categorization levels (e.g., animal/nonanimal; Boucart et al, 2016;Boucart, Moroni, Thibaut, Szaffarczyk, & Greene, 2013). Experimental evidence also indicates that humans can detect animals in peripherally presented natural scenes as far as 758 eccentricity while subjects are fixating centrally (S. J.…”

The contributions of central and peripheral vision to scene-gist recognition with a 180° visual field

“…These functional differences are numerous and multifaceted, including a rapid drop-off in visual resolution with retinal eccentricity (Loschky, McConkie, Yang, & Miller, 2005;Wilkinson, Anderson, Bradley, & Thibos, 2016); increasing difficulty in recognizing objects with increasing eccentricity, especially when they are flanked by other objects (Ehinger & Rosenholtz, 2016;Herzog, Sayim, Chicherov, & Manassi, 2015;Levi, 2008;Nelson & Loftus, 1980;Whitney & Levi, 2011); and a decrease in color sensitivity with eccentricity (Anderson, Mullen, & Hess, 1991;Hansen, Pracejus, & Gegenfurtner, 2009;Nagy & Wolf, 1993;Rovamo & Iivanainen, 1991). Nevertheless, there is also recent evidence that peripheral vision can be very useful for a number of visual tasks, including (surprisingly) recognition of objects and faces if they are relatively large (Boucart et al, 2016), place localization (Eberhardt, Zetzsche, & Schill, 2016), hazard detection during driving (Huestegge & Böckler, 2016), and scene-gist recognition (Boucart, Moroni, Thibaut, Szaffarczyk, & Greene, 2013;Ehinger & Rosenholtz, 2016;Larson & Loschky, 2009). In sum, research on the roles of central and peripheral vision in natural-scene perception has shown that while peripheral vision is very poor compared to central vision, it also very useful, if the tasks and stimuli are sufficiently well specified.…”

The contribution of color information to rapid face categorization in natural scenes

“…For example, Edmonds (2003, 2005) found that, in manual response tasks, the time to detect a face in a scrambled natural scene was shorter with diagnostic color in the scene than with a grayscale, or huereversed, display, although diagnostic color information was not necessary to make a face pop out. In a saccadic choice task, Boucart et al (2016) found that colored faces presented in the visual periphery were categorized more accurately, but not significantly faster, than grayscale faces. In a visual search task for faces in natural scenes (using manual responses), Bindemann and Burton (2009) suggested that a color advantage was restricted to the presence of diagnostic color in the entire face image, as they found that performance (both response time and accuracy) was worse when detecting faces of which only half (either left or right) was in color and the other half in grayscale, than when detecting full-color faces.…”