Locality-sensitive-hashing-based high-dimensional indexing method for large-scale multimedia data

The invention relates to a locality-sensitive-hashing-based high-dimensional indexing method for large-scale multimedia data. The method includes the following steps of extracting high-dimensional features of the multimedia data at the offline indexing stage; establishing an internal storage index, storing the multimedia high-dimensional features in a feature storage area, calculating the locality sensitive hashing vectors of the high-dimensional features, and storing feature numbers and the locality sensitive hashing vectors corresponding to the features in a hashing list storage area, wherein the internal storage index comprises the feature storage area and the hashing list storage area; establishing a first-stage disk index, wherein the first-stage disk index comprises a feature storage area, an index storage area and a plurality of hashing list storage areas; establishing a second-stage disk index, wherein the second-stage disk index comprises a hashing barrel storage area; repeatedly executing the steps mentioned above till all multimedia input is indexed. At the online query stage, features of the multimedia data used for queries are extracted, the queries are conducted on the basis of the established indexes, and similar query results are returned. By means of the method, the scheduling performance of internal storage and disks is improved, and the indexing speed and the retrieving speed of the multimedia data are increased.