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2010
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Constrained Energy Minimization for Matching-Based Image Recognition

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Constrained Energy Minimization for Matching-Based Image Recognition
We propose to use energy minimization in MRFs for matching-based image recognition tasks. To this end, the Tree-Reweighted Message Passing algorithm is modified by geometric constraints and efficiently used by exploiting the guaranteed monotonicity of the lower bound within a nearest-neighbor based classification framework. The constraints allow for a speedup linear to the dimensionality of the reference image, and the lower bound allows to optimally prune the nearestneighbor search without loosing accuracy, effectively allowing to increase the number of optimization iterations without an effect on runtime. We evaluate our approach on well-known OCR and face recognition tasks and on the latter outperform current state-of-the-art.
Tobias Gass, Philippe Dreuw, Hermann Ney
Added 23 Jun 2010
Updated 23 Jun 2010
Type Conference
Year 2010
Where ICPR
Authors Tobias Gass, Philippe Dreuw, Hermann Ney
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