Name
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-12568-8_108 | PROGRESS IN PATTERN RECOGNITION IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2014 |
Keywords | Field | DocType |
video summarization, optimum-path forest, clustering | Data mining,Automatic summarization,Computer science,Robustness (computer science),Visual descriptors,Classifier (linguistics),Cluster analysis | Conference |
Volume | ISSN | Citations |
8827 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 23 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| g b unesp martins | 1 | 0 | 0.34 |
| l c s unesp afonso | 2 | 0 | 0.34 |
| Daniel Osaku | 3 | 14 | 3.05 |
| Jurandy Almeida | 4 | 431 | 35.15 |
| j papa | 5 | 0 | 0.34 |
| e bayrocorrochano | 6 | 0 | 0.34 |
| edwin r hancock | 7 | 0 | 0.34 |