An efficient and effective video similarity search method
Liuzhang Zhu, Zimian Li, Zheng Cao · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
The increasing popularity of online video share and video-on-demand systems makes video similarity search become a hot research field in content-based video retrieval. There is still no satisfying fast scalable video similarity search method in large database. To solve two challenging problems: similarity measurement and search method, a novel efficient video similarity search approach is proposed in this paper. The video features are represented by image characteristic code based on the statistics of spatial-temporal distribution of video frame sequences. The video similarity is measured based on the calculation of the number of video components. For the scalable computing requirement, an efficient search method via clustering index table was presented by index clustering. The experimental results from the query tests in large database show this method is highly efficient and effective for similar video search.