Profil Entropic Visual Features for Visual Concept Detection in CLEF 2008 Campaign.
Hervé Glotin, Zhong‐Qiu Zhao · CLEF (Working Notes) · 2008
In this task, we used only visual information to implement the VCDT task. We dened and compared two simple projection operators : the harmonic and arithmetic means. We proposed a new kind of compact features based on the entropy of pixels projection. These features, called Prol Entropy Features (PEF), were added to usual color means and variances, and then were fed to SVM classiers for the detection of 17 visual concepts on the IARPR images during the CLEF 2008 campaign. The simple arithmetic mean projection is at the 4th best rank at the ocial test over 53 runs of around 20 laboratories. We show that the harmonic projection gives complementary information, and that its simple early fusion with arithmetic PEF yields to the third best rank system. As the runs of the other teams used state of the art SIFT an color histogram visual features, it could be concluded that PEF are ecien t. Moreover, PEF are fast with around 10 images computed per second on usual pentium.