Identifying Perceptually Salient Features on 2D Shapes

Abstract

Maintaining the local style and scale of 2D shape features during deformation, such as when elongating, compressing, or bending a shape, is essential for interactive shape editing. To achieve this, a necessary first step is to develop a robust classification method able to detect salient shape features, if possible in a hierarchical manner. Our aim is to overcome the limitations of existing techniques, which are not always able to detect what a user immediately identifies as a shape feature. Therefore, we first conduct a user study enabling us to learn how shape features are perceived. We then propose and compare several algorithms, all based on the medial axis transform or similar skeletal representations, to identify relevant shape features from this perceptual viewpoint. We discuss the results of each algorithm and compare them with those of the user study, leading to a practical solution for computing hierarchies of salient features on 2D shapes.