Semantically controlled content-based retrieval of video sequences

In this paper, we present a technique for automatic classification of movies based on their content. This technique analyses shot duration and motion energy of movie trailers to characterize them as Action/Character movies. This approach is then combined with a features-based technique for content-based retrieval of video. Experiments indicate a high retrieval accuracy (greater than 96%) together with semantic-control (Action vs. Character) with this combined approach.

[1]  Thomas P. Minka,et al.  An image database browser that learns from user interaction , 1996 .

[2]  Th. Gevers,et al.  Color Image Invariant Segmentation and Retrieval , 1996 .

[3]  Wallace Martin,et al.  Recent Theories of Narrative , 1986 .

[4]  Giridharan Iyengar,et al.  VideoBook: an experiment in characterization of video , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[5]  B. S. Manjunath,et al.  Content-based search of video using color, texture, and motion , 1997, Proceedings of International Conference on Image Processing.

[6]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[7]  R. Jain,et al.  Visual Information Retrieval Technology A Virage Perspective , 1997 .

[8]  Dragutin Petkovic,et al.  Query by Image and Video Content: The QBIC System , 1995, Computer.

[9]  Edoardo Ardizzone,et al.  JACOB: just a content-based query system for video databases , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[10]  Shih-Fu Chang,et al.  Clustering methods for video browsing and annotation , 1996, Electronic Imaging.

[11]  Wei Xiong,et al.  Query by video clip , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[12]  Anil K. Jain,et al.  Image retrieval using color and shape , 1996, Pattern Recognit..