Purchase this article with an account.
Carlo Fantoni, Walter Gerbino; Contour interpolation by vector-field combination. Journal of Vision 2003;3(4):4. doi: 10.1167/3.4.4.
Download citation file:
© 2016 Association for Research in Vision and Ophthalmology.
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.
This PDF is available to Subscribers Only