Interval Hash Tree: An Efficient Index Structure for Searching Object Queries in Large Image Databases
As image databases grow large in size, index structures for fast navigation become important. In particular, when the goal is to locate object queries in image databases under changes in pose, occlusions and spurious data, traditional index structures used in databases become unsuitable. This paper presents a novel index structure called the interval hash tree, for locating multi-region object queries in image databases. The utility of the index structure is demonstrated for query localization in a large image database.