Static video summarization through Optimum-Path Forest clustering

Actas de congresos

Fecha

2014-01-01

Registro en:

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8827, p. 893-900.

1611-3349

0302-9743

http://hdl.handle.net/11449/168181

2-s2.0-84949130645

Autor

Universidade Estadual Paulista (Unesp)

Universidade de São Paulo (USP)

Universidade Federal de São Carlos (UFSCar)

Institución

Universidade Estadual Paulista (Brasil)

Resumen

This paper introduces the Optimum-Path Forest (OPF) classifier for static video summarization, being its results comparable to the ones obtained by some state-of-the-art video summarization techniques. The experimental section has been conducted using several image descriptors in two public datasets, followed by an analysis of OPF robustness regarding one ad-hoc parameter. Future works are guided to improve OPF effectiveness on each distinct video category.

Materias

Clustering

Optimum-path forest

Video summarization

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