Add to ORKGIn this paper, we present new insights in methods to solve the orientation representation problem in arbitrary dimensions. The gradient structure tensor is one of the most used descriptors for local structure in multi-dimensional images. We will relate its properties to the double angle method (2D) and the Knutsson mapping. We present a general scheme to reduce the dimensionality of the Knutsson mapping and derive some properties of these reduced mappings
In this thesis we investigate the measurement of local properties in multi-dimensional grey-value im...
Structure tensors are a common tool for orientation estimation in image processing and computer visi...
Using the n-dimensional structure tensor, linear symmetries within local neighborhoods of multi-dime...
In this paper, we present new insights in methods to solve the orientation representation problem in...
Abstract. In this paper we present a framework to construct a continu-ous orientation representation...
The structure tensor yields an excellent characterization of the local dimensionality and the corres...
The tensor representation has proven a successful tool as a mean to describe local multi-dimensional...
Estimation of local orientation in images is often posed as the task of finding the minimum variance...
The fundamental problem of finding a suitable representation of the orientation of 3D surfaces is co...
The channel representation is a simple yet powerful representation of scalars and vectors. It is esp...
In this paper it is shown how estimates of local structure and orientation can be obtained using a s...
This paper presents an algorithm for estimation of local curvature from gradients of a tensor field ...
This report describes a fourth order tensor defined on projective spaces which can be used for the r...
Structure tensors are a common tool for orientation estimation in image processing and computer visi...
Image intensity gradients can be encoded in a 2-dimensional channel representation. This report disc...
In this thesis we investigate the measurement of local properties in multi-dimensional grey-value im...
Structure tensors are a common tool for orientation estimation in image processing and computer visi...
Using the n-dimensional structure tensor, linear symmetries within local neighborhoods of multi-dime...
In this paper, we present new insights in methods to solve the orientation representation problem in...
Abstract. In this paper we present a framework to construct a continu-ous orientation representation...
The structure tensor yields an excellent characterization of the local dimensionality and the corres...
The tensor representation has proven a successful tool as a mean to describe local multi-dimensional...
Estimation of local orientation in images is often posed as the task of finding the minimum variance...
The fundamental problem of finding a suitable representation of the orientation of 3D surfaces is co...
The channel representation is a simple yet powerful representation of scalars and vectors. It is esp...
In this paper it is shown how estimates of local structure and orientation can be obtained using a s...
This paper presents an algorithm for estimation of local curvature from gradients of a tensor field ...
This report describes a fourth order tensor defined on projective spaces which can be used for the r...
Structure tensors are a common tool for orientation estimation in image processing and computer visi...
Image intensity gradients can be encoded in a 2-dimensional channel representation. This report disc...
In this thesis we investigate the measurement of local properties in multi-dimensional grey-value im...
Structure tensors are a common tool for orientation estimation in image processing and computer visi...
Using the n-dimensional structure tensor, linear symmetries within local neighborhoods of multi-dime...