Indexing Text and Visual Features for WWW Images

In this paper, we present a novel indexing technique called Multi-scale Similarity Indexing (MSI) to index image’s multi-features into a single one-dimensional structure. Both for text and visual feature spaces, the similarity between a point and a local partition’s center in individual space is used as the indexing key, where similarity values in different features are distinguished by different scale. Then a single indexing tree can be built on these keys. Based on the property that relevant images haves similar similarity values from the center of the same local partition in any feature space, certain number of irrelevant images can be fast pruned based on the triangle inequity on indexing keys. To remove the “dimensionality curse” existing in high dimensional structure, we propose a new technique called Local Bit Stream (LBS). LBS transforms image’s text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local p...

• Type: Conference
• Year: 2005
• Where: APWEB
• Authors: Heng Tao Shen, Xiaofang Zhou, Bin Cui
• Keywords: APWEB 2005, Local Partition, Local Partition Center, Multi-scale Similarity Indexing