Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/103592
Title: Video organizaation : near-duplicate video clustering
Authors: Zhu, Ce
Hung, Tzu-Yi
Yang, Gao
Tan, Yap Peng
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2012
Source: Hung, T. Y., Zhu, C., Yang, G., & Tan, Y. P. (2012). Video organizaation : near-duplicate video clustering. 2012 IEEE International Symposium on Circuits and Systems, 1879-1882.
Abstract: It is not uncommon to see several videos of almost identical content on the internet. These near duplicates, coupled with the sheer number of videos, pose a big challenge to the effective organization of video clips online. We propose an adaptive classification approach to detect near-duplicate versions, and an integrated voting strategy to group clusters and to elect a representative for each cluster. Our proposed methods are based on our observation that near-duplicate videos usually span a small, albeit variable area in the feature space, while videos of different contents are scattered far apart. The classification method aims to select a suitable threshold by maximizing the margin for each video sequence in the similarity space, and the voting scheme focuses on merging subsets with mutual information based on neighbor information and inverted indices. Experimental results on an unconstrained web dataset including over 10000 videos demonstrate the efficacy of the proposed methods.
URI: https://hdl.handle.net/10356/103592
http://hdl.handle.net/10220/16741
DOI: http://dx.doi.org/10.1109/ISCAS.2012.6271637
Rights: © 2012 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Conference Papers

Google ScholarTM

Check

Altmetric

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.