Using cross-media correlation for scene detection in travel videos

Wei Ta Chu, Che Cheng Lin, Jen Yu Yu

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

5 Citations (Scopus)

Abstract

Focusing on travel videos taken in uncontrolled environments and by amateur photographers, we exploit correlation between different modalities to facilitate effective travel video scene detection. Scenes in travel photos, i.e., content taken at the same scenic spot, can be easily determined by examining time information. For a travel video, we extract several keyframes for each video shot. Then, photos and keyframes are represented as a sequence of visual word histograms, respectively. Based on this representation, we transform scene detection into a sequence matching problem. After finding the best alignment between two sequences, we can determine scene boundaries in videos with the help of that in photos. We demonstrate that we averagely achieve a purity value of 0.95 if the proposed method is combined with conventional ones. We show that not only features of visual words aid in scene detection, but also cross-media correlation does.

Original languageEnglish
Title of host publicationCIVR 2009 - Proceedings of the ACM International Conference on Image and Video Retrieval
Pages132-138
Number of pages7
DOIs
Publication statusPublished - 2009
EventACM International Conference on Image and Video Retrieval, CIVR 2009 - Santorini Island, Greece
Duration: 2009 Jul 82009 Jul 10

Publication series

NameCIVR 2009 - Proceedings of the ACM International Conference on Image and Video Retrieval

Conference

ConferenceACM International Conference on Image and Video Retrieval, CIVR 2009
CountryGreece
CitySantorini Island
Period09-07-0809-07-10

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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