Comparison of Various AVEIR Visual Concept Detectors with an Index of Carefulness
Résumé
Visual annotation is still an open issue. The Content Based community admits that
a plurality of features and systems shall be considered. We present in this paper four
very different strategies using not only visual information but also text, to implement
ImageCLEF2009 Photo Annotation Task. The visual features are various, such as HSV,
Gabor, EDGE, SIFT, and some more recent. Then we study each model performances,
and propose a new measure, the Carefulness Index (Q) computed on the histogram of
the model?s outputs. Q seems to be correlated with the model performances.