Automatic logo transition detection in digital video contents

Chang Yu Lu, Myung Cheol Roh, Seung Yeon Kang, Seong Whan Lee

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The amount of user created contents has been increasing rapidly and is associated with a serious copyright problem. Automatic logo detection and recognition in videos is a natural and efficient way of overcoming the copyright problem. However, logos have varying characteristics, which make logo detection and recognition very difficult. Moreover, logo transitions between two different logos exist in one video comprising several video contents. This disrupts the automatic logo detection and recognition. Therefore, in order to improve logo detection, it is necessary to take into account the logo transitions explicitly. This paper proposes an accurate logo transition detection method for recognizing logos in digital video contents. The proposed method accurately segments a video according to logo and efficiently recognizes various types of logos. The experimental results demonstrate the effectiveness of the proposed method for logo detection and video segmentation according to logo.

Original languageEnglish
Pages (from-to)175-187
Number of pages13
JournalPattern Analysis and Applications
Volume15
Issue number2
DOIs
Publication statusPublished - 2012 May 1

Keywords

  • Logo detection and recognition
  • Logo transition detection
  • Sub-video merging
  • Video segmentation based on logos

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition

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