We introduce a method for estimation of rotation invariant local shape descriptors for 3D models. This method follows a successful idea commonly used to obtain rotation invariant descriptors in 2D images, and improves it by tackling the difficulty of the 3 degrees of freedom that exists in 3D models. Our method is simple, yet it achieves high levels of invariance after rotation transformations,...

This report surveys current literature related to statistical shape analysis. There are two paradigms: (1) Models that have no prior knowledge about the shape. They evolve boundary curves in time while maintaining predefined smoothness constraints. (2) Models that have prior knowledge about a fixed shape. They use this knowledge to find object boundaries using the covariance matrix and the aver...

Automatic formal verification of systems composed of a large or even unbounded number of components is difficult as the state space of these systems is prohibitively large. Abstraction techniques automatically construct finite approximations of infinite-state systems from which safe information about the original system can be inferred. We study two abstraction techniques shape analysis, a tech...

Level set based approaches are widely used for image segmentation and object tracking. As these methods are usually driven by low level cues such as intensity, colour, texture, and motion they are not sufficient for many problems. To improve the segmentation and tracking results, shape priors were introduced into level set based approaches. Shape priors are generated by presenting many views a ...

This paper proposes a framework for dealing with several problems related to the analysis of shapes. Two related such problems are the definition of the relevant set of shapes and that of defining a metric on it. Following a recent research monograph by Delfour and Zolésio [11], we consider the characteristic functions of the subsets of R2 and their distance functions. The L2 norm of the differ...

Subject-specific modeling is increasingly important in biomechanics simulation. However, how to automatically create highquality finite element (FE) mesh and how to automatically impose boundary conditionare challenging. This paper presents a statistical atlas based approach for automatic meshing of subject-specific shapes. In our approach, shape variations among a shape population are explicit...

In deformable model segmentation, the geometric training process plays a crucial role in providing shape statistical priors and appearance statistics that are used as likelihoods. Also, the geometric training process plays a crucial role in providing shape probability distributions in methods finding significant differences between classes. The quality of the training seriously affects the fina...