| Texto completo | |
| Autor(es): |
Sousa e Santos, Anderson Carlos
;
Pedrini, Helio
;
IEEE
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC); v. N/A, p. 6-pg., 2017-01-01. |
| Resumo | |
Despite its associated challenges, the development of mechanisms for storing, indexing, transmitting and visualizing multimedia content is crucial in order to efficiently deal with the large amount of data generated by several different sources. Digital video technology has advanced rapidly, such that temporal video segmentation methods for automatically detecting transitions in video sequences play an important role in the content analysis tasks. In this work, we propose and evaluate a video shot boundary detection approach based on the Weber local descriptor. Experiments conducted on different datasets demonstrate the effectiveness of our method, whose results are compared against other approaches of the literature. (AU) | |
| Processo FAPESP: | 14/12236-1 - AnImaLS: Anotação de Imagem em Larga Escala: o que máquinas e especialistas podem aprender interagindo? |
| Beneficiário: | Alexandre Xavier Falcão |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |