Abstract. In this paper, we present an approach for image reconstruction from local phase vectors in the monogenic scale space. The local phase vector contains not only the local p...
Abstract. In this paper, we present a novel method for reducing the computational complexity of a Support Vector Machine (SVM) classifier without significant loss of accuracy. We a...
The well-known and very simple MinOver algorithm is reformulated for incremental support vector classification with and without kernels. A modified proof for its O(t-1/2 ) converge...
Abstract. The Gaussian scale-space is a standard tool in image analysis. While continuous in theory, it is generally realized with fixed regular grids in practice. This prevents th...
An experimental comparison of `Edge-Element Association (EEA)' and `Marginalized Contour (MCo)' approaches for 3D modelbased vehicle tracking in traffic scenes is complic...
Hendrik Dahlkamp, Arthur E. C. Pece, Artur Ottlik,...
Abstract. When an object moves, it covers and uncovers texture in the background. This pattern of change is sufficient to define the object's shape, velocity, relative depth, ...
Theresa Cooke, Douglas W. Cunningham, Heinrich H. ...
We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
Abstract. In this paper image-based techniques for 3D surface reconstruction are presented which are especially suitable for (but not limited to) coplanar light sources. The first...
We propose an approach to categorize real-world natural scenes based on a semantic typicality measure. The proposed typicality measure allows to grade the similarity of an image wi...
We present an approach to discretizing multivariate continuous data while learning the structure of a graphical model. We derive the joint scoring function from the principle of p...