A parallel cross-modal search engine over large-scale multimedia collections with interactive relevance feedback

Indexing web-scale multimedia is only possible by distributing storage and computing efforts. Existing large-scale content-based indexing services mostly do not offer interactive relevance feedback. Here, we propose a running demonstrator of our Cross-Modal Search Engine (CMSE) implementing a query-by-example search strategy with relevance feedback and distributed over a cluster of 20 Dual core machines using MPI. We present the performance gain in terms of interactivity (search time) using a part of the Image-Net collection containing more than one million images as base example.