Fast search method for large-scale video based on distributed LSH

doi:10.7523/j.issn.1002-1175.2013.01.016

Abstract

Abstract:

we propose a fast similarity-based video retrieval method for large-scale video database. This method solves scalability and efficiency problems. First, we extract feature vector set for every video and build index using a distributed memory hash structure, called MD-LSH. Secondly, we calculate the similarity of the relevant videos according to the returned similar frame sets. Finally, we return the sorted similar video list as the query results. Experiments show the effectiveness of the proposed method for large-scale video fast retrieval.

Key words: content-based retrieval, distributed LSH, large-scale video, fast search

CLC Number:

TP391

CAO Hai-Bin, ZHU Ming, FENG Wei-Guo. Fast search method for large-scale video based on distributed LSH[J]. , 2013, 30(1): 106-111.

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