Extraction of significant video summaries by dendrogram analysis

被引:7
作者
Benini, S. [1 ]
Bianchetti, A. [1 ]
Leonardi, R. [1 ]
Migliorati, P. [1 ]
机构
[1] Univ Brescia, DEA SCL, Via Branze 38, I-25123 Brescia, Italy
来源
2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS | 2006年
关键词
vector quantization; clustering methods;
D O I
10.1109/ICIP.2006.312377
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:133 / +
页数:2
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