Shape evolution driven by a perceptually motivated measure

In this paper we introduce a novel concept of shape evolution based on a semi-global shape width measure. It is perceptually motivated and helps us distinguish between different shape parts of varying importance. This measure can be integrated into an adaptive a function in a flexible manner and used to achieve a shape evolution which can be controlled by the relative importance of shape parts (without detecting these parts explicitly). For instance, we can start to smooth out fine details while not blurring the large shape parts, or vice versa. This shape-preserving property cannot be achieved by the popular Gaussian smoothing (evolution based on geometric heat flow) and related variants, whose behavior is controlled by the local curvature alone. Experimental results demonstrate the behavior and power of this new shape evolution scheme.