A NEW ROI GROUPING SCHEMA FOR AUTOMATIC IMAGE ANNOTATION
Rami Albatal, Philippe Mulhem, Yves ChiaramellaAbstract
Regions Of Interest (ROI) are successfully used in automatic image annotation through Bag of Visual Words (BoVW) models. However, the ``flat'' BoVW models ignore potentially relevant topological relationships between the ROI. While several works tried to take into account such relations for Content Based Image Retrieval (CBIR), few works evaluated clearly their effects in the context of automatic image annotation. In this article, we propose to explicit the relationships between ROI in automatic annotation methods in order to evaluate their contributions on the results quality. This is done through a model, called ``phrasing model", that generates groups of ROI called Visual Phrases according to relationships constraints. Based on our phrasing model, we define two kinds of Visual Phrases and we show that taking into account topological ROI relationships can significantly overcome the results of the classical BoVW model.
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