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Discriminative Training for Object Recognition Using Image Patches

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Discriminative Training for Object Recognition Using Image Patches
We present a method for automatically learning discriminative image patches for the recognition of given object classes. The approach applies discriminative training of log-linear models to image patch histograms. We show that it works well on three tasks and performs significantly better than other methods using the same features. For example, the method decides that patches containing an eye are most important for distinguishing face from background images. The recognition performance is very competitive with error rates presented in other publications. In particular, a new
Thomas Deselaers, Daniel Keysers, Hermann Ney
Added 12 Oct 2009
Updated 12 Oct 2009
Type Conference
Year 2005
Where CVPR
Authors Thomas Deselaers, Daniel Keysers, Hermann Ney
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