Towards enhanced compression techniques for efficient high-dimensional similarity search in multimedia databases

Abstract

In this paper, we introduce a new efficient compression technique for high-dimensional similarity search in MMDBS. We propose the Active Vertice Tree which is based on concave cluster geometries. Furthermore, we briefly sketch a model for high-dimensional point alignments and specify basic requirements for high-dimensional cluster shapes. Finally, we compare the Active Vertice Tree with other methods for high-dimensional similarity search in terms of their retrieval performance. © Springer-Verlag Berlin Heidelberg 2002.