Fast search algorithm for short video clips from large video database using a novel histogram feature

Feifei Lee, Koji Kotani, Qiu Chen, Tadahiro Ohmi

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

In this paper, we present a novel fast video search algorithm for large video database. This algorithm is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Combined with active search [4], a temporal pruning algorithm, fast and robust video search can be achieved. The proposed search algorithm has been evaluated by 6 hours of video to search for given 200 video clips which each length is 15 seconds. Experimental results show the proposed algorithm can detect the similar video clip in merely 80ms, and is more accurately and robust against Gaussian noise than conventional fast video search algorithm.

本文言語English
ホスト出版物のタイトル2008 International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2008
ページ1223-1227
ページ数5
DOI
出版ステータスPublished - 2008 12月 1
イベント2008 International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2008 - Vienna, Austria
継続期間: 2008 12月 102008 12月 12

出版物シリーズ

名前2008 International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2008

Other

Other2008 International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2008
国/地域Austria
CityVienna
Period08/12/1008/12/12

ASJC Scopus subject areas

  • 人工知能
  • 計算理論と計算数学
  • ソフトウェア
  • 制御およびシステム工学

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