Contribution of motion parallax to segmentation and depth perception
Author(s) -
Ali Yoonessi,
Curtis L. Baker
Publication year - 2011
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/11.9.13
Subject(s) - parallax , computer vision , segmentation , artificial intelligence , kinetic depth effect , depth perception , motion perception , perception , computer science , observer (physics) , communication , motion (physics) , physics , psychology , neuroscience , quantum mechanics
Relative image motion resulting from active movement of the observer could potentially serve as a powerful perceptual cue, both for segmentation of object boundaries and for depth perception. To examine the perceptual role of motion parallax from shearing motion, we measured human performance in three psychophysical tasks: segmentation, depth ordering, and depth magnitude estimation. Stimuli consisted of random dot textures that were synchronized to head movement with sine- or square-wave modulation patterns. Segmentation was assessed with a 2AFC orientation judgment of a motion-defined boundary. In the depth-ordering task, observers reported which modulation half-cycle appeared in front of the other. Perceived depth magnitude was matched to that of a 3D rendered image with multiple static cues. The results indicate that head movement might not be important for segmentation, even though it is crucial for obtaining depth from motion parallax--thus, concomitant depth perception does not appear to facilitate segmentation. Our findings suggest that segmentation works best for abrupt, sharply defined motion boundaries, whereas smooth gradients are more powerful for obtaining depth from motion parallax. Thus, motion parallax may contribute in a different manner to segmentation and to depth perception and suggests that their underlying mechanisms might be distinct.
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