During decades Distance Transforms have proven to be useful for many image processing applications, and more recently, they have started to be used in computer graphics environments. The goal of this paper is to propose a new technique based on Distance Transforms for detecting mesh elements which are close to the objects' external contour (from a given point of view), and using this information for weighting the approximation error which will be tolerated during the mesh simplification process. The obtained results are evaluated in two ways: visually and using an objective metric that measures the geometrical difference between two polygonal meshes
To solve the problems of the existing point-to-triangle-mesh distance computation algorithm which ru...
AbstractIn image processing, the distance transform (DT), in which each object grid point is assigne...
We introduce a novel rich local descriptor of an image point, we call the (labeled) distance set, wh...
The need to analyze and visualize distances between objects arises in many use cases. Although the...
Complex models generated e.g. with a laser range scanner often consist of several thousand or millio...
Complex models generated e.g. with a laser range scanner often consist of several thousand or millio...
Similarity measurements between 3D objects and 2D images are useful for the tasks of object recognit...
Many spatial datasets and spatial problems can be described with reference to regular lattice framew...
Geometric shapes can be represented in a variety of different ways. A distancemap is a map from poin...
One of the main problems in image analysis is a comparison of different shapes in images. It is ofte...
In many cases the surfaces of geometric models consist of a large number of triangles. Several algor...
The distance transform has found many applications in image analysis. The Euclidean distance transfo...
The need to analyze and visualize differences of very similar objects arises in many research areas:...
In many cases the surfaces of geometric models consist of a large number of triangles. Several algor...
In image processing, the distance transform (DT), in which each object grid point is assigned the di...
To solve the problems of the existing point-to-triangle-mesh distance computation algorithm which ru...
AbstractIn image processing, the distance transform (DT), in which each object grid point is assigne...
We introduce a novel rich local descriptor of an image point, we call the (labeled) distance set, wh...
The need to analyze and visualize distances between objects arises in many use cases. Although the...
Complex models generated e.g. with a laser range scanner often consist of several thousand or millio...
Complex models generated e.g. with a laser range scanner often consist of several thousand or millio...
Similarity measurements between 3D objects and 2D images are useful for the tasks of object recognit...
Many spatial datasets and spatial problems can be described with reference to regular lattice framew...
Geometric shapes can be represented in a variety of different ways. A distancemap is a map from poin...
One of the main problems in image analysis is a comparison of different shapes in images. It is ofte...
In many cases the surfaces of geometric models consist of a large number of triangles. Several algor...
The distance transform has found many applications in image analysis. The Euclidean distance transfo...
The need to analyze and visualize differences of very similar objects arises in many research areas:...
In many cases the surfaces of geometric models consist of a large number of triangles. Several algor...
In image processing, the distance transform (DT), in which each object grid point is assigned the di...
To solve the problems of the existing point-to-triangle-mesh distance computation algorithm which ru...
AbstractIn image processing, the distance transform (DT), in which each object grid point is assigne...
We introduce a novel rich local descriptor of an image point, we call the (labeled) distance set, wh...