Title :
An efficient similarity search algorithm for web video
Author :
Cao, Zheng ; Zhu, Ming
Author_Institution :
Dept. of Autom., Univ. of Sci. & Technol. of China, Hefei, China
Abstract :
The amount of online video is increasing tremendously nowadays. For the convenience of information retrieval, video similarity search has become an important research issue in content-based video retrieval. There is still no satisfying scalable fast similarity search method for large database. In order to solve two challenging problems: similarity measure and fast search, a novel efficient video similarity search algorithm is proposed in this paper. A compact video image signature was computed according to the statistics of spatial-temporal distribution of video frame sequences. The video similarity is measured based on the calculation of the number of similar video components. For the scalable computing requirement, a novel efficient search method based on 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.
Keywords :
Internet; content-based retrieval; image sequences; pattern clustering; video retrieval; Web video; compact video image signature; content-based video retrieval; index clustering; information retrieval; online video; spatial-temporal distribution; video frame sequences; video similarity search algorithm; Clustering algorithms; Content based retrieval; Feature extraction; Image databases; Information retrieval; Search methods; Spatial databases; Statistical distributions; Variable structure systems; Video sharing; clustering index table; image signature; video similarity search;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5357706
