Near-Duplicate Web Video Retrieval and Localization Using Improved Edit Distance
With the development of network,there exists many nearduplicate videos online shared by individuals.These ones cause problems such as copyright infringement and search result redundancy.To solve the issues,this paper proposes a filter-and-refine framework for near-duplicate video retrieval and localization.By regarding video sequences as strings,Edit distance is used and improved in the approach.Firstly,bag-of-words (BOW) model is utilized to measure the similarities between frames.Then,non-near-duplicate videos are filtered out by computing the proposed relative Edit distance similarity (REDS).Next,a dynamic programming strategy is proposed to rank the remained videos and localize the similar segments.Experiments demonstrate the effectiveness and robustness of the method in retrieval and localization.
Near-duplicate video retrieval Near-duplicate video localization Edit distance
Hao Liu Qingjie Zhao Hao Wang Cong Zhang
Beijing Key Lab of Intelligent Information Technology,School of Computer Science and Technology,Beijing Institute of Technology,Beijing,China
国际会议
International Asia-Pacific Web Conference(第18届国际亚太互联网大会)
苏州
英文
141-152
2016-09-23（万方平台首次上网日期，不代表论文的发表时间）