The perception of natural contour.

Abstract

The observation that natural curves and surfaces are often fractal suggests that people may be sensitive to their statistical properties. The perceptual protocols that underlie discrimination between fractals and between other types of random contour and fractals are examined. Discrimination algorithms that have precisely the same sensitivities as human observers are constructed. These algorithms do not recognize the integrated scale hierarchy intrinsic to fractal form and operate by imposing a metatheory of structure that is based on a signal-noise distinction. The success of the algorithms implies that (a) self-affinity in random fractals is not perceptually recovered and (b) people have a natural disposition to view contour in terms of signal and noise. The authors propose that this disposition be understood as a principle of perceptual organization.

Fractal Architecture Could Be Good for You

“…A common answer is that the natural world -and the way it changes over time -is also characterized by pink noise, which suggests that our fractal minds are optimized to process the fractal characteristics of natural scenes (see, for example, [Knill et al 1990]). This hypothesis is supported by the finding that discriminating fractal contours is best for those that have the same (fractal) properties as natural scenes [Gilden et al 1993]. Interestingly, these findings can (tentatively) explain the creation of fractal artwork, and fractal architecture in particular.…”

Architectural Lessons from Environmental Psychology: The Case of Biophilic Architecture

“…Some authors propose that, because of its fractal nature, the brain is optimized to process the statistical characteristics of natural scenes, which are also found to be governed by 1/f spectra (e.g., Knill, Field, & Kersten, 1990). For instance, Gilden, Schmuckler, and Clayton (1993) found that discriminating fractal contours was best for those sharing (statistical) properties with natural scenes. Consistent with this is the finding that neurons in the V1 area of the brain show a preference for 1/f signals (Yu, Romero, & Lee, 2005).…”

Provenance of correlations in psychological data

“…Aligned with this distinction is whether a process is scale free or governed by a controlling time scale. Fractal noises have a symmetry referred to as self-affinity (Mandelbrot, 1985), and this property entails both the absence of discernible scales and the presence of longrange correlations (see Gilden, Schmuckler, & Clayton, 1993;Mandelbrot, 1983;Maylor, Chater, & Brown, 2001;Schroeder, 1991, and the references therein). The exact sense in which time scales and the range of correlations intertwine will be discussed in detail below.…”