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- Filip Korč
- 2008

We investigate Discriminative Random Fields (DRF) which provide a principled approach for combining local discriminative classifiers that allow the use of arbitrary overlapping features, with adaptive data-dependent smoothing over the label field. We discuss the differences between a traditional Markov Random Field (MRF) formulation and the DRF model, and… (More)

We consider the problem of inference in a graphical model with binary variables. While in theory it is arguably preferable to compute marginal probabilities, in practice researchers often use MAP inference due to the availability of efficient discrete optimization algorithms. We bridge the gap between the two approaches by introducing the Discrete Marginals… (More)

- Filip Korc, Václav Hlavác
- Human Motion
- 2006

This work contributes to detection and tracking of walking or running humans in surveillance video sequences. We propose a 2D model-based approach to the whole body tracking in a video sequence captured from a single camera view. An extended six-link biped human model is employed. We assume that a static camera observes the scene horizontally or obliquely.… (More)

- Filip Korc, Wolfgang Förstner
- DAGM-Symposium
- 2008

We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the parameter likelihood gradient. We show, as opposed to [1][2], that these parameter learning methods can be improved and evaluate the resulting performance employing different inference… (More)

- Sabine D. Bauer, Filip Korč, Wolfgang Förstner
- Precision Agriculture
- 2011

Three methods of automatic classification of leaf diseases are described based on high-resolution multispectral stereo images. Leaf diseases are economically important as they can cause a loss of yield. Early and reliable detection of leaf diseases has important practical relevance, especially in the context of precision agriculture for localized treatment… (More)

- Filip Korc, Wolfgang Förstner
- IWCIA Special Track on Applications
- 2008

We present a solution to the following discrete optimization problem. Given a set of independent, possibly overlapping image regions and a non-negative likeliness of the individual regions, we select a nonoverlapping subset that is optimal with respect to the following requirements: First, every region is either part of the solution or has an overlap with… (More)

We present a fast automatic reproducible method for 3d semantic segmentation of magnetic resonance images of the knee. We formulate a single global model that allows to jointly segment all classes. The model estimation was performed automatically without manual interaction and parameter tuning. The segmentation of a magnetic resonance image with 11 Mio… (More)

- Filip Korc
- 2012

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