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...

Shape is one of the most important visual attributes used to characterize objects, playing a important role in pattern recognition. There are various approaches to extract relevant information of a shape. An approach widely used in shape analysis is the complexity, and Fractal Dimension and Multi-Scale Fractal Dimension are both well-known methodologies to estimate it. This papers presents a co...

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...

Digital representation of three dimensional curves is considered. Two dimensional representation schemes are rst reviewed, then methods applicable to curves in three and higher dimensional spaces are described. Desirable properties of curve representation schemes are identiied and used as a basis for qualitative and quantitative comparison of the various methods that have been suggested. Conclu...

In Western countries, the growing population of seniors brings us to think about new healthcare systems to ensure the safety of elderly people at home. Falls are one of the greatest risk for seniors living alone. Computer vision provides a promising solution to analyze people behavior and detect some unusual events like falls. In this paper, we propose to detect falls by analyzing the human sha...

The present work shows a novel fractal dimension method for shape analysis. The proposed technique extracts descriptors from a shape by applying a multi-scale approach to the calculus of the fractal dimension. The fractal dimension is estimated by applying the curvature scale-space technique to the original shape. By applying a multi-scale transform to the calculus, we obtain a set of descripto...

This paper presents some basics for the analysis of point clouds using the geometrically intuitive mathematical framework of conformal geometric algebra. In this framework it is easy to compute with osculating circles for the description of local curvature. Also methods for the fitting of spheres as well as bounding spheres are presented. In a nutshell, this paper provides a starting point for ...

This paper proposes a novel algorithm for individual recognition by gait. The method of Procrustes shape analysis is used to produce Procrustes Mean Shape (PMS) as a compressed representation of gait sequence. PMS is adopted as the gait signature in this paper. Instead of using the Procrustes mean shape distance as a similarity measure, we introduce shape context descriptor to measure the simil...

The 2D Fourier Descriptor is an elegant and powerful technique for 2D shape analysis. This paper intends to extend such technique to 3D. Though conceptually natural, such an extension is not trivial in that two critical problems, the spherical parametrization and invariants construction, must be solved. By using a newly developed surface parametrization method–the discrete conformal mapping (DC...

We analyze the properties of the norm of the commutator of two Hermitian matrices, showing that asymptotically it behaves like a metric, and establish its relation to joint approximate diagonalization of matrices, showing that almost-commuting matrices are almost jointly diagonalizable, and vice versa. We show an application of our results in the field of 3D shape analysis.