The Venetian blind effect and the mechanisms of early stereopsis
William W. Stine,
University of New Hampshire, USA
Joshua J. Dobias,
Rutgers University, USA
Richard S. Hetley,
University of California - Irvine, USA
John E. Sparrow,
University of New Hampshire at Manchester, USA
When a square-wave grating is viewed binocularly with either an average luminance disparity or a contrast disparity, the bars of the grating will appear to rotate out of the fronto-parallel plane. Perceived rotation due to average luminance or contrast disparities, which has been called the Venetian blind effect, can be cancelled by introducing a geometric disparity. While irradiation can induce a perceived geometric disparity at high-contrast edges, such disparities fail to account for the Venetian blind effect with moderate contrasts since (i) the predicted change in apparent rotation that should accompany edge blurring fails to materialize and (ii) the processing of average luminance and contrast disparities takes roughly four times that of geometric disparities. Hence, neurophysiological mechanisms would seem to be implicated in the Venetian blind effect. Further, individual differences suggest variation in the strength of the input from each eye to those mechanisms.
Consequently, in addition to geometrically-based, classical, or Wheatstone stereopsis and da Vinci stereopsis, the Venetian blind effect represents a third condition under which depth is perceived as a function of binocular disparity. With this research topic, we hope to encourage a deeper understanding of the physiology underlying the Venetian blind effect, the effect’s relationship to other mechanisms of early stereopsis, individual differences in the processing of luminance and contrast disparities with possible relationships to amblyopia, and the implications these results have for the design of binocular imaging devices. Manuscripts reporting original behavioral and/or physiological research in humans or non-humans, as well as theoretical perspectives, review articles, and mathematical models/meta-analyses are welcome.