The pyramid-technique: towards breaking the curse of dimensionality
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Indexing the edges—a simple and yet efficient approach to high-dimensional indexing
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Indexing the Distance: An Efficient Method to KNN Processing
Proceedings of the 27th International Conference on Very Large Data Bases
Making the Pyramid Technique Robust to Query Types and Workloads
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Towards effective indexing for very large video sequence database
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Evaluation campaigns and TRECVid
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
KpyrRec: a recursive multidimensional indexing structure
International Journal of Parallel, Emergent and Distributed Systems
Clustering by random projections
ICDM'07 Proceedings of the 7th industrial conference on Advances in data mining: theoretical aspects and applications
Supporting aspect-based video browsing: analysis of a user study
Proceedings of the ACM International Conference on Image and Video Retrieval
Simulated evaluation of faceted browsing based on feature selection
Multimedia Tools and Applications
A novel retrieval framework using classification, feature selection and indexing structure
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
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In the last few years, the increase of online video has challenged research in the field of video information retrieval. Video search engines have become common on the Internet and require the use of powerful tools for fast access to data. However the representation of multimedia data as video shot or keyframe with visual features requires the use of a multidimensional space and indexing structures face the well known ``curse of dimensionality". In this paper, we propose a new indexing structure that combines a clustering algorithm using random projections and a recursive multidimensional indexing structure. In our experiments, we study the effeciency and the effectiveness of our indexing structure using visual features of video shots of TRECVID database. We compare our proposed structure with other state-of-the-art methods.