This monograph reviews both the theory and practice of the numerical computation of
geodesic distances on Riemannian manifolds. The notion of Riemannian manifold allows …

This paper discusses certain modifications of the ideas concerning the Gromov–Hausdorff
distance which have the goal of modeling and tackling the practical problems of object …

The computer vision and pattern recognition communities have recently witnessed a surge
of feature-based methods in object recognition and image retrieval applications. These …

We present an algorithm for the automatic alignment of two 3D shapes (data and model),
without any assumptions about their initial positions. The algorithm computes for each …

In architectural freeform design, the relation between shape and fabrication poses new
challenges and requires more sophistication from the underlying geometry. The new …

Differential invariants of curves and surfaces such as curvatures and their derivatives play a
central role in Geometry Processing. They are, however, sensitive to noise and minor …

Data-driven methods serve an increasingly important role in discovering geometric,
structural, and semantic relationships between shapes. In contrast to traditional approaches …

Feature-based methods have recently gained popularity in computer vision and pattern
recognition communities, in applications such as object recognition and image retrieval. In …

Invariant shape descriptors are instrumental in numerous shape analysis tasks including
deformable shape comparison, registration, classification, and retrieval. Most existing …

Geometry processing algorithms often require the robust extraction of curvature information.
We propose to achieve this with principal component analysis (PCA) of local …