Static Video Summarization through Optimum-Path Forest Clustering
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Data
2014-01-01
Autores
Martins, G. B. [UNESP]
Afonso, L. C. S. [UNESP]
Osaku, D.
Almeida, Jurandy
Papa, João Paulo [UNESP]
Título da Revista
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Editor
Springer
Resumo
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.
Descrição
Palavras-chave
video summarization, optimum-path forest, clustering
Como citar
Progress In Pattern Recognition Image Analysis, Computer Vision, And Applications, Ciarp 2014. Berlin: Springer-verlag Berlin, v. 8827, p. 893-900, 2014.