Titlebook: Computer Analysis of Images and Patterns; 15th International C Richard Wilson,Edwin Hancock,William Smith Conference proceedings 2013 Sprin

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https://doi.org/10.1007/978-3-7643-8675-7models such as Hidden Markov Models or Conditional Random Fields, whose quality is measured through character and word error rates while they are usually not trained to optimize such criterion. We propose an efficient method for learning Hidden Conditional Random Fields to optimize the error rate wi

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Parametrizing ,,(,): Singular Casel commonly used alternatives. In this paper, we study the separability properties of this kernel and we propose a way to compute a low-dimensional kernel embedding where the separation of the different classes is enhanced. The idea stems from the observation that the multidimensional scaling embeddi

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Die Grundschulwahl in Deutschlanddetect and segment human body regions by jointly embedding parts and pixels. For all extracted segments the appearance and shape models are learned in order to automatically extract the foreground objects across a sequence of video frames. We evaluated the framework using a challenging set of video

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