| Full text | |
| Author(s): |
Martins, G. B.
;
Afonso, L. C. S.
;
Osaku, D.
;
Almeida, Jurandy
;
Papa, J. P.
;
BayroCorrochano, E
;
Hancock, E
Total Authors: 7
|
| Document type: | Journal article |
| Source: | PROGRESS IN PATTERN RECOGNITION IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2014; v. 8827, p. 8-pg., 2014-01-01. |
| 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. (AU) | |
| FAPESP's process: | 12/06472-9 - Exploring Contextual Classification Approaches for Optimum-Path Forest |
| Grantee: | Daniel Osaku |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 13/20387-7 - Hyperparameter optimization in deep learning arquitectures |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Scholarships abroad - Research |