%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/07.09.16.32
%2 sid.inpe.br/sibgrapi/2016/07.09.16.32.44
%@doi 10.1109/SIBGRAPI.2016.053
%T Temporal- and Spatial-Driven Video Summarization Using Optimum-Path Forest
%D 2016
%A Martins, Guilherme Brandão,
%A Papa, João Paulo,
%A Almeida, Jurandy Gomes de,
%@affiliation Sao Paulo State University
%@affiliation Sao Paulo State University
%@affiliation Federal University of Sao Carlos
%E Aliaga, Daniel G.,
%E Davis, Larry S.,
%E Farias, Ricardo C.,
%E Fernandes, Leandro A. F.,
%E Gibson, Stuart J.,
%E Giraldi, Gilson A.,
%E Gois, João Paulo,
%E Maciel, Anderson,
%E Menotti, David,
%E Miranda, Paulo A. V.,
%E Musse, Soraia,
%E Namikawa, Laercio,
%E Pamplona, Mauricio,
%E Papa, João Paulo,
%E Santos, Jefersson dos,
%E Schwartz, William Robson,
%E Thomaz, Carlos E.,
%B Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)
%C São José dos Campos, SP, Brazil
%8 4-7 Oct. 2016
%I IEEE Computer Society´s Conference Publishing Services
%J Los Alamitos
%S Proceedings
%K Optimum-Path Forest, Video Summarization.
%X Video summarization aims at generating reduced representations for fast and effective video retrieval and classification. In this paper, we cope with such problem by proposing a temporal- and spatial-driven approach that makes use of the Optimum-Path Forest (OPF) clustering to automatic find the number of keyframes, as well as to extract them to compose the final summary. The experiments in two public datasets show OPF can outperform very recent results, thus achieving a performance comparable to some state-of-the-art techniques.
%@language en
%3 paper.pdf