Movement-induced motion signal distributions in outdoor scenes

Abstract

The movement of an observer generates a characteristic field of velocity vectors on the retina (Gibson 1950). Because such optic flow-fields are useful for navigation, many theoretical, psychophysical and physiological studies have addressed the question how ego-motion parameters such as direction of heading can be estimated from optic flow. Little is known, however, about the structure of optic flow under natural conditions. To address this issue, we recorded sequences of panoramic images along accurately defined paths in a variety of outdoor locations and used these sequences as input to a two-dimensional array of correlation-based motion detectors (2DMD). We find that (a) motion signal distributions are sparse and noisy with respect to local motion directions; (b) motion signal distributions contain patches (motion streaks) which are systematically oriented along the principal flow-field directions; (c) motion signal distributions show a distinct, dorso-ventral topography, reflecting the distance anisotropy of terrestrial environments; (d) the spatiotemporal tuning of the local motion detector we used has little influence on the structure of motion signal distributions, at least for the range of conditions we tested; and (e) environmental motion is locally noisy throughout the visual field, with little spatial or temporal correlation; it can therefore be removed by temporal averaging and is largely over-ridden by image motion caused by observer movement. Our results suggest that spatial or temporal integration is important to retrieve reliable information on the local direction and size of motion vectors, because the structure of optic flow is clearly detectable in the temporal average of motion signal distributions. Ego-motion parameters can be reliably retrieved from such averaged distributions under a range of environmental conditions. These observations raise a number of questions about the role of specific environmental and computational constraints in the processing of natural optic flow.

Depth, contrast and view-based homing in outdoor scenes

“…Potentially the most serious constraint on using memorized images for homing in the natural world is the temporal variability of views due to the movement of the sun, the movements of clouds, the movements of wind-driven vegetation and the resulting movements of shadows (Zeil et al 2003;Zanker and Zeil 2005). Möller (2002) recently suggested a colour opponent representation as one possible way in which visual representations can be made immune against changes in illumination, by emphasising the contrast between terrestrial objects and the sky.…”

Motion perception and visual signal design in Anolis lizards

“…The 2DMD model is a Matlab implementation of the model described in Zanker & Zeil (2005). The basic features are summarized in figure 1.…”

“…The most widely used model of EMD response is known as a 'correlation detector' (Reichardt 1961;Borst & Egelhaaf 1993), which has been used successfully to predict motion detection responses in a variety of invertebrate and vertebrate animals (Borst & Egelhaaf 1989, 1993Dror et al 2001;Borst 2007;Meso & Zanker 2009). This approach has been expanded to a model consisting of a two-dimensional grid of interconnected EMDs, referred to as a two-dimensional visual-motion detection (2DMD) model, used to study the perception of the motion patterns embedded in complex natural scenes (Zeil & Zanker 1997;Eckert & Zeil 2001;Zanker & Zeil 2005). Pallus et al (2010) used a computational 2DMD model (based on Zanker & Zeil 2005) to study motion perception in the lizard Anolis sagrei.…”

“…This approach has been expanded to a model consisting of a two-dimensional grid of interconnected EMDs, referred to as a two-dimensional visual-motion detection (2DMD) model, used to study the perception of the motion patterns embedded in complex natural scenes (Zeil & Zanker 1997;Eckert & Zeil 2001;Zanker & Zeil 2005). Pallus et al (2010) used a computational 2DMD model (based on Zanker & Zeil 2005) to study motion perception in the lizard Anolis sagrei. Behaviour experiments were used to determine appropriate spatial and temporal parameters for the model.…”

Quantifying Ecological Constraints on Motion Signaling

“…The use of motion detector algorithms for quantifying animal signals is now the standard way to compare display movements and plant motion noise (Zanker and Zeil, 2005;Fleishman and Pallus, 2010;Pallus et al, 2010). However, all these studies utilize video footage from a single camera view that necessarily assumes the camera is ideally positioned to sample the display.…”