The Fourier Descriptor (FD) is a powerful tool for shape analysis and many signatures have been proposed to derive Fourier descriptors. These shape signatures lack of important information in articulation and part structures of complex shapes. In this study, the Inner-Centroid Distance (ICDs) signature which is based on the Centroid Distance signature and Inner-Distance is developed to overcome...

The paper describes a method for identification of mechanisms and process trends based on combination of subject-driven document clustering, shape analysis, trends understanding and relevant context retrieval via semantic analysis. The goal is to extract potentially interesting knowledge from a set of technical information based on analysis of graphical information in order to find explanation ...

Shape grammars are, in general, intractable. Even amongst tractable shape grammars, their characteristics vary significantly. This paper describes a paradigm for practical general shape grammar interpreters, which aim to address computational difficulties posed by parameterization. The paradigm is expressed in terms of frameworks each comprising an underlying data structure, manipulation algori...

We present a shape analysis for programs that manipulate overlaid data structures which share sets of objects. The abstract domain contains Separation Logic formulas that (1) combine a per-object separating conjunction with a per-field separating conjunction and (2) constrain a set of variables interpreted as sets of objects. The definition of the abstract domain operators is based on a notion ...

We consider the problem of learning an object model for feature matching. The matching system is Bayesian in nature with separate likelihood and prior parts. The likelihood is based on Gabor filter responses, which are modelled as probability distributions in the filter response vector space. The prior model for the object shape is learnt in two stages: in the first stage we assume only the mea...

Figure 1: We present a view-based convolutional network that produces local, point-based shape descriptors. The network is trained such that geometrically and semantically similar points across different 3D shapes are embedded close to each other in descriptor space (left). Our produced descriptors are quite generic — they can be used in a variety of shape analysis applications, including dense...

Finding point correspondence in anatomical images is a key step in shape analysis and deformable registration. This paper proposes an automatic correspondence detection algorithm using wavelet-based attribute vectors defined on every image voxel. The attribute vector reflects the anatomical characteristics in a large neighborhood around the respective voxel. It plays the role of a morphological...

This article for the first time develops a nonparametric methodology for the analysis of projective shapes of configurations of landmarks on real 3D objects from their regular camera pictures. A fundamental result in computer vision, emulating the principle of human vision in space, claims that, generically, a finite 3D configuration of points can be retrieved from corresponding configurations ...

Reeb graphs provide a method for studying the shape of a manifold by encoding the evolution and arrangement of level sets of a simple Morse function defined on the manifold. Since their introduction in computer graphics they have been gaining popularity as an effective tool for shape analysis and matching. In this context one question deserving attention is whether Reeb graphs are robust agains...