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Carlo Fantoni, Walter Gerbino; Contour interpolation by vector-field combination. Journal of Vision 2003;3(4):4. doi: https://doi.org/10.1167/3.4.4.
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© ARVO (1962-2015); The Authors (2016-present)
We model the visual interpolation of missing contours by extending contour fragments under a smoothness constraint. Interpolated trajectories result from an algorithm that computes the vector sum of two fields corresponding to different unification factors: the good continuation (GC) field and the minimal path (MP) field. As the distance from terminators increases, the GC field decreases and the MP field increases. Viewer-independent and viewer-dependent variables modulate GC-MP contrast (i.e., the relative strength of GC and MP maximum vector magnitudes). Viewer-independent variables include the local geometry as well as more global properties such as contour support ratio and shape regularity. Viewer-dependent variables include the retinal gap between contour endpoints and the retinal orientation of their stems. GC-MP contrast is the only free parameter of our field model. In the case of partially occluded angles, interpolated trajectories become flatter as GC-MP contrast decreases. Once GC-MP contrast is set to a specific value, derived from empirical measures on a given configuration, the model predicts all interpolation trajectories corresponding to different types of occlusion of the same angle. Model predictions fit psychophysical data on the effects of viewer-independent and viewer-dependent variables.
Models can be evaluated by considering the sensitivity (S) or invariance (I) of predicted interpolation trajectories with respect to local and contextual variables.
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