A dynamic content-based indexing method for multimedia databases: hierarchical cellular tree

This paper presents a novel indexing technique, hierarchical cellular tree, which is designed to bring an effective solution especially for indexing on large-scale multimedia databases. A pre-emptive cell search mechanism is introduced in order to prevent the corruption of large multimedia item collections due to the limited discrimination obtained from the visual and aural descriptors. In addition to this, the similar items are focused within appropriate cellular structures, which will be the subject to mitosis operations when the dissimilarity emerges as a result of irrelevant item insertions. Mitosis operations ensure to keep the cells in a focused and compact form and yet the cells can grow into any dimension as long as the compactness prevails. The proposed indexing scheme is then optimized for a novel query method, the progressive query, in order to maximize the retrieval efficiency for the user point of view. Experimental results show that the speed of the retrievals is significantly improved.