Investigation Of The Effectiveness Of Cross-Media Indexing

Cross-media analysis and indexing leverage the individual potential of each indexing information provided by different modalities, such as speech, text and image, to improve the effectiveness of information retrieval and filtering in later stages. The process does not only constitute generating a merged representation of the digital content, such as MPEG-7, but also enriching it in order to help remedy the imprecision and noise introduced during the low-level analysis phases. It has been hypothesized that a system that combines different media descriptions of the same multi-modal audio-visual segment in a semantic space will perform better at retrieval and filtering time. In order to validate this hypothesis, we have developed a cross-media indexing system which utilises the Multiple Evidence approach by establishing links among the modality specific textual descriptions in order to depict topical similarity.