Sampling Strategies for Bag-of-Features Image Classification
Lecture notes in computer sciencePublished 1 January 2006Open access
Éric Nowak, Frédéric Jurie, Bill Triggs
Citations906
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TL;DR
It is shown experimentally that for a representative selection of commonly used test databases and for moderate to large numbers of samples, random sampling gives equal or better classifiers than the sophisticated multiscale interest operators that are in common use.
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