Near-Duplicate Video Retrieval and Localization Using Relative Levenshtein Distance Similarity

Qing Jie Zhao, Hao Wang*, Hao Liu, Cong Zhang

*此作品的通讯作者

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摘要

To effectively retrieve and locate near-duplicate videos, a novel approach of video retrieval and localization was proposed based on relative Levenshtein Distance similarity (LD). In the algorithm, two major components were included, named local descriptor based video coding and relative Levenshtein Distance similarity-based video retrieval and localization. About the local descriptor based video coding, the video key-frames were extracted firstly from data base; then Root-SIFT feature descriptors were extracted from key-frames and all descriptors were clustered to generate a codebook with the Hierarchical K-Means; lastly, each key-frame was assigned a unique visual word and code. About the relative Levenshtein Distance similarity-based video retrieval and localization, each query video was encoded firstly, and then the near-duplicate videos were filtrated, near-duplicate segments were located, and the retrieved videos were re-ranked with the relative Levenshtein Distance similarity-based algorithm. The experimental results show that the LD algorithm can achieve a 8.55% higher effect on the average F1 evaluation criterion than the algorithm proposed by Yeh et.al, and the NDCR is reduced to 29%.

源语言英语
页(从-至)85-90
页数6
期刊Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
38
1
DOI
出版状态已出版 - 1 1月 2018

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Zhao, Q. J., Wang, H., Liu, H., & Zhang, C. (2018). Near-Duplicate Video Retrieval and Localization Using Relative Levenshtein Distance Similarity. Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 38(1), 85-90. https://doi.org/10.15918/j.tbit1001-0645.2018.01.015