Adaptive Relevance Feedback For Fusion Of Text And Visual Features

It has been shown that query can be correlated with its context to a different extent; in this case the feedback images. We introduce an adaptive weighting scheme where the respective weights are automatically modified, depending on the relationship strength between visual query and its visual context and textual query and its textual context; the number of terms or visual terms (mid-level visual features) co-occurring between current query and its context. The user simulation experiment has shown that this kind of adaptation can indeed further improve the effectiveness of hybrid CBIR models.