We propose a probabilistic segmentation scheme, which is widely applicable to some extend. Besides the segmentation itself our model incorporates object specific shading. Dependent...
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
Abstract. This paper proposes a regression-based method for singleimage super-resolution. Kernel ridge regression (KRR) is used to estimate the high-frequency details of the underl...
This paper demonstrates how a simple, yet effective, set of features enables to integrate ensemble classifiers in optical flow based tracking. In particular, gray value differences...
In this work we propose two novel vector quantization (VQ) designs for discrete HMM-based on-line handwriting recognition of whiteboard notes. Both VQ designs represent the binary ...