A survey of technologies and algorithms for parsing and indexing multimedia databases
A survey of technologies and algorithms for parsing and indexing multimedia databases. Conventional database systems are designed for managing textual and numerical data, and retrieving such data is often based on simple comparisons of text/numerical values. The digitized representation of images, video, or data by itself does not fully represent the contents of the multimedia items, users have to manually add semantic data to fully describe content. The content-based retrieval methods take these intrinsic values into account. Content-based retrieval of multimedia database calls for content-based indexing techniques. Querying multimedia data is costly and appropriate indexing is required. Efficient indexing of high dimensional feature vectors is important to allow content based query applications to perform efficiently on large databases. In this survey, I give an overview of the advances on algorithms for indexing multimedia data, identify the problems of processing queries in high-dimensional space, and recommend the best multimedia data features to be used for indexing. The main contribution of this research is to identify and recommend the commonly used methods of indexing multimedia data by collating available algorithms.