The conservation of biodiversity within tropical forest regions does not lie only in the maintenance of natural forest areas, but on conservation strategies directed toward agricultural land types within which they are embedded. This study investigated variations in bird assemblages of different functional groups of forest-dependent birds in three agricultural land types, relative to distance f...

Shape analysis is a fundamental and difficult problem in computer vision. It is crucial for recognition, video tracking, image retrieval and other applications. This paper proposes 2D shape analysis by using geodesic distance. It focuses on how to apply geodesic distance for shape matching and shape decomposition. Geodesic Fourier Descriptors is developed as a kind of shape representation for s...

quantifying spatial structure is one of the most important components, describing natural ecosystems and their biodiversity. in this study, a set of indices and functions related to spatial structure using 102 established plots with an area of 1000 m2 were presented. to achieve spatial structure of carpinus-fagus type, a set of indices (clark & evans, uniform angle, shannon-wiener, mingling and...

In this paper we introduce a versatile and robust method for analyzing the feature space associated with a given surface. The method is based on the mean-shift operator which was shown to be successful in image and video processing. Its strength stems from the fact that it works in a single space of joint geometry and attributes called the feature-space. The feature-space attributes can be scal...

Here by isometric we mean that the geodesic distance between pairs of points on the non-convex polyhedron is always equal to the geodesic distance between of the corresponding pairs of points on a cube. Alternatively, it means that two surfaces can be triangulated in such a way that they now consist of congruent triangles which are glued according to the same combinatorial rules. For example, i...

We propose a new approach to compute geodesic distance transformations in arbitrary 2D and 3D domains. The distance transformation proposed here is robust and has proved to have a computational complexity linear in the domain size. Our scheme is based on a new technique which we call occlusion points propagation, and with a higher accuracy than other geodesic distance transformations proposed b...

We find an upper bound for geodesic distances associated to monotone Riemannian metrics on positive definite matrices and density matrices.

Abstract. The present paper discusses the question of formulating and solving minimal-distance problems over the group-manifold of real symplectic matrices. In order to tackle the related optimization problem, the real symplectic group is regarded as a pseudo-Riemannian manifold and a metric is chosen that affords the computation of geodesic arcs in closed forms. Then, the considered minimal-di...