From video shot clustering to sequence segmentation

Segmenting video documents into sequences from elementary shots to supply an appropriate higher level description of the video is a challenging task. The paper presents a two-stage method. First, we build a binary agglomerative hierarchical time-constrained shot clustering. Second, based on the cophenetic criterion, a breaking distance between shots is computed to detect sequence changes. Various options are implemented and compared. Real experiments have proved that the proposed criterion can be efficiently used to achieve appropriate segmentation into sequences.

[1]  Wolfgang Effelsberg,et al.  Scene Determination Based on Video and Audio Features , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[2]  Alan Hanjalic,et al.  Automatically Segmenting Movies into Logical Story Units , 1999, VISUAL.

[3]  Paul England,et al.  Comparison of automatic video segmentation algorithms , 1996, Other Conferences.

[4]  Anil K. Jain,et al.  Algorithms for Clustering Data , 1988 .

[5]  Boon-Lock Yeo,et al.  Extracting story units from long programs for video browsing and navigation , 1996, Proceedings of the Third IEEE International Conference on Multimedia Computing and Systems.

[6]  Giridharan Iyengar,et al.  Models for automatic classification of video sequences , 1997, Electronic Imaging.

[7]  John R. Kender,et al.  Video scene segmentation via continuous video coherence , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[8]  Brian Everitt,et al.  Clustering of large data sets , 1983 .

[9]  Alexander G. Hauptmann,et al.  Text, Speech, and Vision for Video Segmentation: The InformediaTM Project , 1995 .

[10]  Peter J. Rousseeuw,et al.  CLUSTERING LARGE DATA SETS , 1986 .

[11]  François Pachet,et al.  Using Description Logics for Indexing Audiovisual Documents , 1998, Description Logics.

[12]  Philippe Aigrain,et al.  Medium knowledge-based macro-segmentation of video into sequences , 1997 .

[13]  John S. Boreczky,et al.  A hidden Markov model framework for video segmentation using audio and image features , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).