Experimental result analysis for a generative probabilistic image retrieval model

Abstract

The main conclusion from the metrics-based evaluation of video retrieval systems at TREC's video track is that non-interactive image retrieval from general collections using visual information only is not yet feasible. We show how a detailed analysis of retrieval results -- looking beyond mean average precision (MAP) scores on topical relevance -- gives significant insight in the main problems with the visual part of the retrieval model under study. Such an analytical approach proves an important addition to standard evaluation measures.