Abstract. We present a novel model for object recognition and detection that follows the widely adopted assumption that objects in images can be represented as a set of loosely cou...
Thomas Deselaers, Andre Hegerath, Daniel Keysers, ...
In real world scenes, objects to be classified are usually not visible from every direction, since they are almost always positioned on some kind of opaque plane. When moving a cam...
Abstract. We present a method for 3D object modeling and recognition which is robust to scale and illumination changes, and to viewpoint variations. The object model is derived fro...
The present paper considers the supplement of prior knowledge about joint angle configurations in the scope of 3-D human pose tracking. Training samples obtained from an industrial...
Thomas Brox, Bodo Rosenhahn, Uwe G. Kersting, Dani...
Independent Component Analysis (ICA) is a frequently used preprocessing step in source localization of MEG and EEG data. By decomposing the measured data into maximally independent...
Peter Breun, Moritz Grosse-Wentrup, Wolfgang Utsch...
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Abstract. We propose to tackle the optical flow problem by a combination of two recent advances in the computation of dense correspondences, namely the incorporation of image segme...
Michael Bleyer, Christoph Rhemann, Margrit Gelautz
We demonstrate the use of a "smart camera" to accelerate two very different image processing applications. The smart camera consists of a high quality video camera and f...
Cellular Neural Networks are widely used with real-time image processing's applications. Such systems can be efficiently realized using macro enriched fieldprogrammable gate-...
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...