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

Authors:
Marc von Wyl;Hisham Mohamed;Eric Bruno;Stephane Marchand-Maillet
Affiliations:
University of Geneva, Carouge, Switzerland;University of Geneva, Carouge, Switzerland;University of Geneva, Carouge, Switzerland;University of Geneva, Carouge, Switzerland
Venue:
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Year:
2011

Citing 6
Cited 4

FastMap: a fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets

SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Combining multimodal preferences for multimedia information retrieval

Proceedings of the international workshop on Workshop on multimedia information retrieval
MapReduce: simplified data processing on large clusters

Communications of the ACM - 50th anniversary issue: 1958 - 2008
Design of Multimodal Dissimilarity Spaces for Retrieval of Video Documents

IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving Bag-of-Features for Large Scale Image Search

International Journal of Computer Vision
Building a web-scale image similarity search system

Multimedia Tools and Applications

Multimedia information retrieval in a social context

PROMISE'12 Proceedings of the 2012 international conference on Information Retrieval Meets Information Visualization
MRO-MPI: MapReduce overlapping using MPI and an optimized data exchange policy

Parallel Computing
Distributed media indexing based on MPI and MapReduce

Multimedia Tools and Applications
Retrieval of high-dimensional visual data: current state, trends and challenges ahead

Multimedia Tools and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.