Skimming rushes video using retake detection

ABSTRACT

In audiovisual post-production users are confronted with large amounts of redundant unedited raw material, called rushes. Viewing and organizing this material is a crucial but time consuming task. This paper describes an approach for creating skimmed versions of the rushes video based on the elimination of unusable content and clustering of takes. Typically multiple, but slightly differing takes of the same scene can be found in the rushes video. We propose a method for clustering takes of one scene shot from the same camera position. It uses a variant of the LCSS algorithm to find matching subsequences in sequences of extracted features from the source video. The approach is evaluated by two subjective measures for the quality of the skim and by measuring the overlap between items found in the source video and the skim.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.1 Multimedia Information Systems

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Abstracting methods
      H.3.3 Information Search and Retrieval

General Terms:
Algorithms, Experimentation

Keywords:
TRECVID, content abstraction, retake, rushes, summarization, video skim