%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2024/02.22.19.17
%2 sid.inpe.br/sibgrapi/2024/02.22.19.17.49
%T Supervoxel Approach in an Efficient Multiscale Object-Based Framework
%D 2023
%A Lacerda, Lucca S. P.,
%A Cunha, Felipe D.,
%A Guimarães, Silvio J. F.,
%@affiliation Pontifícia Universidade Católica de Minas Gerais
%@affiliation Pontifícia Universidade Católica de Minas Gerais
%@affiliation Pontifícia Universidade Católica de Minas Gerais
%E Clua, Esteban Walter Gonzalez,
%E Körting, Thales Sehn,
%E Paulovich, Fernando Vieira,
%E Feris, Rogerio,
%B Conference on Graphics, Patterns and Images, 36 (SIBGRAPI)
%C Rio Grande, RS
%8 Nov. 06-09, 2023
%S Proceedings
%K Supervoxel Computation, Image Segmentation, Image Foresting Transform, Object Saliency Map.
%X The use of supervoxel segmentation has shown substantial provement in video analysis because it can improve object delineation and reduce computer workload. In this work, we have used SICLE (Superpixel Through Iterative Clearcutting), which is an innovative graph-based superpixel framework that makes multi-scale segmentation by exploiting object information. For segmenting videos, we changed the graph creation step. The framework has exceeded state-of-the-art approaches, and its results precisely delineate the object of interest.
%@language en
%3 2023_conf_sibgrapi_wuw_lucca_video.pdf