Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2007.Thesis (Master's) -- Bilkent University, 2007.Includes bibliographical references leaves 87-92.In this thesis, we propose a new method to search different instances of a
video sequence inside a long video. The proposed method is robust to view point
and illumination changes which may occur since the sequences are captured in
different times with different cameras, and to the differences in the order and
the number of frames in the sequences which may occur due to editing. The
algorithm does not require any query to be given for searching, and finds all
repeating video sequences inside a long video in a fully automatic way. First, the
frames in a video are ranked according to their similarity on the distribution of
salient points and colour values. Then, a tree based approach is used to seek for
the repetitions of a video sequence if there is any. These repeating sequences are
pruned for more accurate results in the last step.
Results are provided on two full length feature movies, Run Lola Run and
Groundhog Day, on commercials of TRECVID 2004 news video corpus and on
dataset created for CIVR Copy Detection Showcase 2007. In these experiments,
we obtain %93 precision values for CIVR2007 Copy Detection Showcase dataset
and exceed %80 precision values for other sets.Can, TolgaM.S
