The uncrowded window of object recognition

Abstract

It is now emerging that vision is usually limited by object spacing rather than size. The visual system recognizes an object by detecting and then combining its features. 'Crowding' occurs when objects are too close together and features from several objects are combined into a jumbled percept. Here, we review the explosion of studies on crowding-in grating discrimination, letter and face recognition, visual search, selective attention, and reading-and find a universal principle, the Bouma law. The critical spacing required to prevent crowding is equal for all objects, although the effect is weaker between dissimilar objects. Furthermore, critical spacing at the cortex is independent of object position, and critical spacing at the visual field is proportional to object distance from fixation. The region where object spacing exceeds critical spacing is the 'uncrowded window'. Observers cannot recognize objects outside of this window and its size limits the speed of reading and search.Object recognition means calling a chair a chair, despite variations in style, viewpoint, rendering and surrounding clutter. Crowding is a breakdown of object recognition.Let us begin by sketching a popular two-step model of object recognition: feature detection and combination. Features are components of images that are detected independently 1-4 . They are typically simple and nonoverlapping. The first step in object recognition is feature detection 4 . Each neuron in the primary visual cortex responds when a feature matches its receptive field. Only the features that drive neurons hard enough are detected 5 . In the second step, the brain combines some of the detected features to recognize the object. This combining step (including 'integration', 'binding', 'segmentation', 'pooling', 'grouping', 'contour integration' and 'selective attention') is still mysterious 3,4,6-11 . Some objects are recognized through a single combining of features over the whole object, whereas other objects require separate combining over each of several regions of the object 12-14 . These distinct regions define object parts. In an object with multiple parts, each part must be recognized before they are all joined together.The best evidence that features are indivisible elements that we detect and combine is that, even with practice, people combine information across features much less well than within a feature. Searching for a conjunction of several features is usually much harder than searching for a single feature 3 . Despite reading a billion letters over a lifetime, people still recognize letters inefficiently, by detecting and combining many simple features rather than by detecting each letter as a whole 4,15 . Crowding is inappropriate feature combination that spoils object recognition (reviewed in refs. 16,17 ).

Music and words in the visual cortex: The impact of musical expertise

“…Following brain lesions, such encoding may be lost, resulting in "note-by-note" reading (Stanzione et al, 1990). Expertise in word reading involves analogous perceptual tuning, namely reading-selective reduction of crowding (Huckauf and Nazir, 2007; M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT Pelli and Tillman, 2008), and synthetic perception of complex objects such as frequent groups of letters (Vinckier et al, 2007;Grainger and Ziegler, 2011).…”

Effects of word frequency and visual complexity on eye movements of young and older Chinese readers

“…This includes a progressive loss of sensitivity to visual detail (e.g., Crassini, Brown, & Bowman, 1988;Elliott, Yang, & Whitaker, 1995;Owsley, Sekuler, Siemsen, 1983), which has been shown previously to affect normal reading performance for alphabetic languages Paterson, McGowan & Jordan, 2013a,b). In addition, older adults typically experience increased effects of visual crowding (McCarley, Yamani, Kramer, & Mounts, 2012;Scialfa, Cordazzo, Bubric, & Lyon, 2013), characterised by reduced ability to recognise visual objects in clutter, especially in peripheral vision (Bouma, 1971; see also Pelli & Tillman, 2008). In A c c e p t e d M a n u s c r i p t…”

Examining Crowding Using a Real Three-Dimensional Experimental Setup

“…Thus, at this critical spacing there occurs no crowding anymore, that is, target recognition performance for flanked and isolated targets does not differ. This window, in which crowding occurs, thus the spatial extent of crowding, increases proportionally with increasing target eccentricity (Pelli and Tillman, 2008).…”