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Peter Bex, Anita Simmers, Steven Dakin; Integration of moving contours from local directional signals. Journal of Vision 2002;2(7):655. doi: 10.1167/2.7.655.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose: The movement of spatial structure that extends over large areas of visual space is thought to be analysed by a battery of local directional analysers. However, little is known about how such local signals are integrated to represent the motion of individual objects. Here we examine the detection of moving spatial structure embedded in random moving noise.
Methods. Stimuli were a field of pseudo-randomly positioned Difference of Gaussian elements. Background elements were randomly positioned and moved in random directions. Contour elements were constrained to fall on a notional contour whose length, curvature, element spacing and motion were under experimental control. The contours were defined only by the relative motions of the elements forming them and were not visible on single movie frames.
Results. The detectability of moving contours increased with the number and proximity of elements defining them, in agreement with studies of static images. Unlike static images, detectability was unaffected by the curvature of the contour. Contours that moved in directions orthogonal or parallel (open black arrows) to the mean contour orientation (broken line) were more detectable than those moving in intermediate directions (solid black arrows), but the most detectable were non-rigid contours, whose elements moved along the length of the contour (white arrows).
Conclusions. The detectability of moving structure embedded in moving noise shares some of the spatial grouping principles that have been identified for static contours. However, a number of differences and the high visibility of non-rigid contours, suggest that the grouping of motion cues to object structure obey different principles and possibly different architecture.
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