dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.contributor | Universidade de São Paulo (USP) | |
dc.contributor | Universidade Federal de São Carlos (UFSCar) | |
dc.date.accessioned | 2018-12-11T16:40:07Z | |
dc.date.available | 2018-12-11T16:40:07Z | |
dc.date.created | 2018-12-11T16:40:07Z | |
dc.date.issued | 2014-01-01 | |
dc.identifier | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8827, p. 893-900. | |
dc.identifier | 1611-3349 | |
dc.identifier | 0302-9743 | |
dc.identifier | http://hdl.handle.net/11449/168181 | |
dc.identifier | 2-s2.0-84949130645 | |
dc.description.abstract | 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. | |
dc.language | eng | |
dc.relation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | |
dc.relation | 0,295 | |
dc.rights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | Clustering | |
dc.subject | Optimum-path forest | |
dc.subject | Video summarization | |
dc.title | Static video summarization through Optimum-Path Forest clustering | |
dc.type | Actas de congresos | |