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Akiko Yasuoka, Shinichi Kita, Masahiro Ishii; Apparent depth of a patch of dynamic random noise within a static field of random dots. Journal of Vision 2015;15(12):832. doi: 10.1167/15.12.832.
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© ARVO (1962-2015); The Authors (2016-present)
A patch with one texture appears as a distinct perceptual entity within a background region with contrasting texture if their features differ adequately (texture segregation). If there is no pictorial depth cue such as size, the patch, which is a small closed region, may stand out. Incidentally, if two fields of random dots that are identical except for a slight shift in a region are presented in rapid alternation, the region appears as an entity reciprocating above the background (RDK). With these phenomena, a number of studies have attempted to reveal several types of perception such as texture, subjective contour, or motion. While Klymenko et al. (1989) reported that a flickering region appeared as a background when the temporal frequency was high, most studies have not focused on depth perception. This study investigates apparent depth of a patch of dynamic random noise within a static field of random dots. Dynamic random noise involves spatiotemporal changes and stimulates motion detectors. In this regard, it differs from flickering stimuli. An experiment was conducted to determine the appearance. The disparate region was depicted with dynamically changed random dots (2.5, 5, or 10 fps) and the remaining region was depicted with static random dots. Each dot was white on a black background. The disparate region subtended 3.7x3.7 deg. We asked subjects to judge apparent depth of the patch. The results indicated that the disparate region tended to appear through an aperture if the refresh rate of dynamic random noise was 10 fps. Another experiment was conducted to estimate the perceived depth using a depth nulling technique. Binocular disparity was used to null the perceived depth. We found the perceived depth was about 0.5-1.0 arcmin of binocular disparity.
Meeting abstract presented at VSS 2015
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