Temporal gradient pattern for the near-duplicate video clustering

Hyundeok Lee, Hyeran Byun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a near-duplicate video clustering method based on temporal gradient pattern (TGP). Most related work that extract feature from video ignored temporal changes of video. To solve this problem we propose feature extraction method that used temporal changes of video that is the most important feature at video. Temporal gradient pattern is extracted from a shot video and patterned by temporal changes of frames within a shot video. We proposed the method that can cluster near-duplicate video effectively and quickly using the temporal gradient pattern. Experiments have performed for speed, feature extraction and video clustering evaluation. Proposed method shows good performance to represent videos using proposed feature extraction method, clustering method can obtain good performance and speed also is good.

Original languageEnglish
Title of host publication2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
Pages3186-3189
Number of pages4
DOIs
Publication statusPublished - 2010 Nov 15
Event2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010 - Qingdao, China
Duration: 2010 Jul 112010 Jul 14

Publication series

Name2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
Volume6

Other

Other2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
CountryChina
CityQingdao
Period10/7/1110/7/14

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Human-Computer Interaction

Cite this

Lee, H., & Byun, H. (2010). Temporal gradient pattern for the near-duplicate video clustering. In 2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010 (pp. 3186-3189). [5580710] (2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010; Vol. 6). https://doi.org/10.1109/ICMLC.2010.5580710