Depth perception of illusory surfaces

Abstract

The perception of an illusory surface, a subjectively perceived surface that is not given in the image, is one of the most intriguing phenomena in vision. It strongly influences the perception of some fundamental properties, namely, depth, lightness and contours. Recently, we suggested (1) that the context-sensitive mechanism of depth computation plays a key role in creating the illusion, (2) that the illusory lightness perception can be explained by an influence of depth perception on the lightness computation, and (3) that the perception of variations of the Kanizsa figure can be well-reproduced by implementing these principles in a model (Kogo, Strecha, et al., 2010). However, depth perception, lightness perception, contour perception, and their interactions can be influenced by various factors. It is essential to measure the differences between the variation figures in these aspects separately to further understand the mechanisms. As a first step, we report here the results of a new experimental paradigm to compare the depth perception of the Kanizsa figure and its variations. One of the illusory figures was presented side-by-side with a non-illusory variation whose stereo disparities were varied. Participants had to decide in which of these two figures the central region appeared closer. The results indicate that the depth perception of the illusory surface was indeed different in the variation figures. Furthermore, there was a non-linear interaction between the occlusion cues and stereo disparity cues. Implications of the results for the neuro-computational mechanisms are discussed.

Optimal combination of illusory and luminance-defined 3-D surfaces: A role for ambiguity

“…He concluded their combination is represented by a mixture model that allows prior models to differ between observers depending on their interpretation of sensory cues. Recently, N. Kogo, Drozdzewska, Zaenen, Alp, and Wagemans (2014) assessed the perceived depth of planar Kanizsa figures by varying the structure and polarity of the inducers and compared the perceived depth to similar Kanizsa-like figures with inducers that do not create illusory boundaries. They proposed a nonlinear dynamic weighting model to describe the combination of occlusion cues and depth from binocular disparity in Kanizsa configurations, which suggests consistent cues may work together to enhance depth perception of illusory surfaces and reduce the ambiguity of individual cues.…”

Distance Deception by Fragmented Objects: How Figures May Alter the Perceived Depth of the Background

“…When looking at this figure, we experience something suspended, floating, a phenomenology that we do not find when we turn our gaze to Figure 1a. Here the illusory figure is mainly defined by illusory contours and enhanced brightness, attributes that do not characterize the illusory figures in Figure 1b and c. A dissociation of the attributes of the illusory figures has already been observed (Parks & Marks, 1985; Kogo et al, 2014).…”

“…More than 40 years after the first investigations (Coren, 1972; Kogo et al, 2014), the depth issue related to the illusory figures still arouses interest. However, it is curious that this phenomenon has been circumscribed to a unique observational contest, that is, the white surface with the four pacmen as inducers.…”

“…Kogo et al (2010, 2014) assume that what they name the “depth map of an image” consists in a computation based on the border ownership assignment: “the properties of the images that influence border ownership may also influence illusory depth perception” (Kogo et al, 2014, p. 63). Burge et al (2010) and Bertamini and Wagemans (2013) provide important contributions for the understanding of the relation between contour curvature and figure/ground and depth order assignment.…”

Nonsymbolic numerosity in sets with illusory-contours exploits a context-sensitive, but contrast-insensitive, visual boundary formation process

“…The reference patterns were composed by 12 “Pac-Man” like items but half of the items were drawn in white (RGB = 1, 1, 1) and the other half in black (RGB = −1, −1, −1). As in the first experiment, test patterns contained a variable numerosity (from 9 to 15 “Pac-Man” like items), but those containing an even numerosity (10, 12, 14) were constructed with an equal number of black and white inducers on a mid-gray background (e.g., Kogo et al, 2014 ), whereas test stimuli with odd numerosity (9, 11, 13, 15) were counterbalanced, containing one free inducer in excess drawn in black in half of the patterns (four random visual patterns) and drawn in white in the other half (four random visual patterns). Note that aligned inducers forming the ICs in test stimuli had always one black and one white inducer (see Fig.…”