Kernel Descriptors in comparison with Hierarchical Matching Pursuit
نویسنده
چکیده
In this paper a state of the art sparse coding algorithm for image classification, namely Hierachical Matching Pursuit(HMP), is compared to state of the art algorithms using kernel methods(Efficient Match Kernels, Kernel Descriptors and Hierarchical Kernel Descriptors). HMP is faster and achieves slightly better results than the other algorithms when run over several test-sets. But on the downside, there are set-ups, where the performance of HMP declines. We review and explain all four algorithms and investigate, in which set-ups HMP shouldn’t be applied.
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