Measuring Convexity for Figure/Ground Separation

In human perception, convex surfaces have a strong tendency to be perceived as the "figure". Convexity has a stronger influence on figural organization than other global shape properties, such as symmetry ([9]). And yet, there has been very little work on convexity properties in computer vision. We present a model for figure/ground segregatation which exhibits a preference for convex regions as the figure (i.e., the foreground). The model also shows a preference for smaller regions to be selected as figures, which is also known to hold for human visual perception (e.g., Koffka [11]). The model is based on the machinery of Markov random fields/random walks/diffusion processes, so that the global shape properties are obtained via local and stochastic computations. Experimental results demonstrate that our model performs well on ambiguous figure/ground displays which were not captured before. In particular, in ambiguous displays where neither region is strictly convex, the mode...

• Type: Conference
• Year: 1999
• Where: ICCV
• Authors: Hsing-Kuo Pao, Davi Geiger, Nava Rubin
• Keywords: Computer Vision, Convex Regions, Convexity Properties, Global Shape Properties, Human Visual Perception, ICCV 1999, Model Shows Preference