A biologically plausible model of human shape symmetry perception

Abstract

Symmetry is usually computationally expensive to encode reliably, and yet it is relatively effortless to perceive. Here, we extend F. J. A. M. Poirier and H. R. Wilson's (2006) model for shape perception to account for H. R. Wilson and F. Wilkinson's (2002) data on shape symmetry. Because the model already accounts for shape perception, only minimal neural circuitry is required to enable it to encode shape symmetry as well. The model is composed of three main parts: (1) recovery of object position using large-scale non-Fourier V4-like concentric units that respond at the center of concentric contour segments across orientations, (2) around that recovered object center, curvature mechanisms combine multiplicatively the responses of oriented filters to encode object-centric local shape information, with a preference for convexities, and (3) object-centric symmetry mechanisms. Model and human performances are comparable for symmetry perception of shapes. Moreover, with some improvement of edge recovery, the model can encode symmetry axes in natural images such as faces.

Behind the Looking-Glass: A Review on Human Symmetry Perception

“…Importantly, it is also in line with symmetry models at other levels of description. In particular, its quantification of the amount of symmetry largely agrees with van der Helm and Leeuwenberg's holographic approach (see [128] for details).…”

“…A comprehensive spatial filtering model was recently introduced by Poirier and Wilson [128]. In contrast to the previous models, this model is sensitive to symmetry of the outline of a stimulus.…”

Brain Activity in Response to Visual Symmetry

“…Other studies, however, have found poor performance for detection of anti-symmetry with dense arrays [42]. A more recent type of filter model has been able to extend the response of the model to closed contours and to faces [43]. In alternative to filter models, other authors have worked on models that extract structural information [5,44].…”

Symmetry perception by poultry chicks and its implications for three-dimensional object recognition

“…Similarly, symmetry preference could arise from generalization from multiple views of a given object, and it allows detection and recognition of objects from novel viewpoints [15,16,22,23]. One might expect symmetry detection to involve long-range comparisons of potentially conjugate points in the image, but this process is computationally costly and it has been proposed that symmetry is a local feature comparable with edges and lines [17,[24][25][26].…”

“…A limitation of nearly all theoretical and experimental studies of symmetry perception is that they consider twodimensional bilateral symmetry in fronto-parallel view, normally with a vertical axis of symmetry [26]. Selfevidently, bilaterally symmetrical patterns and objects do not normally produce a symmetrical retinal image.…”