In the current video analysis scenario, effective summarization of video sequences through shot clustering facilitates the access to the content and helps in understanding the associated semantics. This paper introduces a generic scheme to produce hierarchical summaries of the video document starting from a dendrogram representation of clusters of shots. The evaluation of the cluster distortions, and the exploitation of the dependency relationships between clusters on the dendrograms, allow to obtain only a few semantically 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, using and comparing different visual features on color information. Results are evaluated in terms of metrics that measure the content representational value of the summarization technique.

Hierarchical Video Summaries by Dendrogram Cluster Analysis

BENINI, Sergio;LEONARDI, Riccardo;MIGLIORATI, Pierangelo
2006-01-01

Abstract

In the current video analysis scenario, effective summarization of video sequences through shot clustering facilitates the access to the content and helps in understanding the associated semantics. This paper introduces a generic scheme to produce hierarchical summaries of the video document starting from a dendrogram representation of clusters of shots. The evaluation of the cluster distortions, and the exploitation of the dependency relationships between clusters on the dendrograms, allow to obtain only a few semantically 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, using and comparing different visual features on color information. Results are evaluated in terms of metrics that measure the content representational value of the summarization technique.
2006
Proceedings of the 2006 European Signal Processing Conference (EUSIPCO 2006)
Ateneo di appartenenza
PE6_11 Machine learning, statistical data processing and applications using signal processing (eg. speech, image, video)
PE7_7 Signal processing
PE6_8 Computer graphics, computer vision, multi media, computer games
Esperti anonimi
Inglese
no
2006 European Signal Processing Conference (EUSIPCO 2006)
4-8 September 2006
Firenze, Italy
Internazionale
ELETTRONICO
UNICO
1
5
5
EURASIP
Hierachical video summaries; Video indexing
no
open
Benini, Sergio; Bianchetti, A; Leonardi, Riccardo; Migliorati, Pierangelo
273
info:eu-repo/semantics/conferenceObject
4
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/14895
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