Title :
Extraction of Significant Video Summaries by Dendrogram Analysis
Author :
Benini, S. ; Bianchetti, A. ; Leonardi, R. ; Migliorati, P.
Author_Institution :
DEA-SCL, Brescia Univ., Italy
Abstract :
In the current video analysis scenario, effective clustering of shots facilitates the access to the content and helps in understanding the associated semantics. This paper introduces a cluster analysis on shots which employs dendrogram representation to produce hierarchical summaries of the video document. Vector quantization codebooks are used to represent the visual content and to group the shots with similar chromatic consistency. The evaluation of the cluster codebook distortions, and the exploitation of the dependency relationships on the dendrograms, allow to obtain only a few significant summaries of the whole video. Finally the user can navigate through summaries and decide which one best suites his/her needs for eventual post-processing. The effectiveness of the proposed method is demonstrated by testing it on a collection of video-data from different kinds of programmes. Results are evaluated in terms of metrics that measure the content representational value of the summarization technique.
Keywords :
feature extraction; image representation; vector quantisation; video coding; chromatic consistency; cluster codebook distortion; dendrogram representation; vector quantization codebook; video document; video summary extraction; visual content representation; Clustering methods; Distortion measurement; Graph theory; Multimedia databases; Navigation; Nonlinear distortion; Performance analysis; Testing; Tree graphs; Vector quantization; Vector quantization; clustering methods;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.312377