Efficient and effective state-based framework for news video retrieval
Zheng, Aihua, Ma, Jixin, Zhou, Xiaoyi and Luo, Bin (2010) Efficient and effective state-based framework for news video retrieval. International Journal of Advancements in Computing Technology, 2 (4). pp. 151-161. ISSN 2005-8039 (Print), 2233-9337 (Online) (doi:10.4156/ijact.vol2.issue4.16)Full text not available from this repository.
In this paper, an efficient and effective framework is proposed for news video retrieval. Firstly, the 64-dimensional colour histogram is extracted as the feature vector. Then the pair quantizer is adopted to transfer the news video retrieval problem into multi-dimensional string matching problem, which conduces to the efficiency to the framework. Secondly, a new measurement named ‘optimal temporal common subsequence’, which distinguishes the difference caused by rich temporal characteristics including temporal order, temporal duration and temporal gap, is designed to match state-sequence, followed by the point & interval-based formal characterization of time-series and state-sequences. Thirdly, we tested the proposed measurement on news video retrieval. The performance shows the proposed algorithm is more effective for news video retrieval.
|Uncontrolled Keywords:||state-sequence matching, optimal temporal common subsequence, news video retrieval|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|School / Department / Research Groups:||School of Computing & Mathematical Sciences
Faculty of Architecture, Computing & Humanities > School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Department of Computer Science
Faculty of Architecture, Computing & Humanities > School of Computing & Mathematical Sciences > Department of Computer Science
|Last Modified:||10 May 2013 15:05|
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